Kaggle Competitions Download Marketing Dataset

keerth516 6-Nov-13 6:19am. Like you have to login and join a competition before you download the dataset, you have to create a token for authentication. This dataset could be used to produce some interesting liguistic insights about the type of language used in different news articles or to simply identify tags for untracked news articles. The competition lasted three months and ended a few weeks ago. Vesta Corporation provided the dataset for this competition. Datasets - Cars - World and regional statistics, national data, maps, rankings. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. This is just like the "Datasets" tab, where you can click on the competition and download the data for your models. com: News analysis and commentary on information technology trends, including cloud computing, DevOps, data analytics, IT leadership, cybersecurity, and IT infrastructure. The goals of this competition are to advance the state-of-the-art in 3D object detection. This challenge was to predict the number of votes, comments, and views that issues created on See Click Fix would get. Look for datasets without too many rows and columns, because those are easier to work with. , Pedreschi, D. Revisiting the Relationship between Competition and Price Discrimination by Ambarish Chandra and Mara Lederman. A Fortune 100 company, Liberty Mutual Insurance has provided a wide range of insurance products and services designed to meet their customers' ever-changing needs for over 100 years. The Nielsen datasets at the Kilts Center for Marketing is a relationship between the University of Chicago Booth School of Business and the Nielsen Company and makes comprehensive marketing datasets available to academic researchers around the world. What should you do? Update your dataset, of course! This short video will show up how to. Exploring and reading other Kagglers' code is a great way to both learn new techniques and stay involved in the community. Data Set Information: * Audio track (encoded as mp3) of each of the 106,574 tracks. So here's a brief description of a Dataiku marketers first Kaggle competition - and remember, this Dataiku marketer is me, and I'm no techy. Call the DataSet. In the paper, the authors evaluate 179 classifiers arising from 17 families across 121 standard datasets from the UCI machine learning repository. Hacking GTA V for Carvana Kaggle Challenge very non-trivial solutions are born as a result of tough competition. The dataset is available in the scikit-learn library, or you can also download it from the UCI Machine Learning Library. Total downloads of all papers by Pradeep K. Cannot download large datasets over the kaggle API how to list completed competitions with kaggle API? #209 opened Aug 20, 2019 by appleyuchi. Implemented A random forest classifier as the features were mostly ordinal so as to find the best model a tree version is to be implemented. The first Asian Cup was held in Hong Kong in 1975 and was held every two years until 2010. using ML and DL, I have worked on developing a pipeline for predicting full-body, especially face sparse shape point transforms from the text data and using this pipeline for getting the understanding of any type of contextual data by a human 3D model. In this competition, we introduce a new dataset of 211 fine-grained (prepared) food categories with 101733 training images collected from the web. They also allow you to share code and analysis in Python or R. com/adarsh8986/ chatbot_using_python. Datasets produced by government agencies or non-profit organizations can usually be downloaded free of charge. (Remember, this is not a ideal candidate for demonstrate capabilities of Spark. MTG-UPF and Google collaborate to foster open research in sound event recognition Big Data, Data Science, Knowledge Extraction, Research, Barcelona, Maria de Maeztu. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. However, the preferred option is to use Anaconda. Google is definitely your friend with any question about things online but a lot of the highest quality data sources don’t necessarily show up at the top in a Google search. They provide a "Getting Started" competition to gain a first experience in Data Science with Titanic Kaggle. Since MNIST restricts us to 10. * Nine audio features (consisting of 518 attributes) for each of the 106,574 tracks. You can submit a research paper, video presentation, slide deck, website, blog, or any other medium that conveys your use of the data. We develop a computational framework for predicting business performance that takes into account both intrinsic (e. The Corpus of Linguistic Acceptability (CoLA) in its full form consists of 10657 sentences from 23 linguistics publications, expertly annotated for acceptability (grammaticality) by their original authors. On the other hand using, for example, IPFS or a torrent would be better, because you can reference the dataset using a global identifier and anyone can easily get access to it. !kaggle datasets list Others information like size of the dataset and download count is also available in the details. Submit a Prediction to Kaggle for the First Time Published by Josh on November 2, 2017 This tutorial walks you through submitting a ". Relevant Papers: N/A. Download the dataset directly to Google Drive via Google Colab. These datasets are available for download and can be used to create your own recommender systems. The dataset provided by State Farm was comprised of photos of drivers described as “2D dashboard camera images. Flexible Data Ingestion. Kaggle is a fun way to practice your machine learning skills. Download the dataset from Kaggle https: What is Anomaly Detection In data science, anomaly detection is the identification of rare items, events or observations. One should have tried a few beginner’s problems before getting into the advanced problems. Call the DataSet. Public Datasets on Google Cloud Platform makes it easy for users to access and analyze data in the cloud. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. So you've created a Kaggle dataset but you have new data to upload or you want to change one of your files. 6, pytorch1. csv” file of predictions to Kaggle for the first time. There are many types of competitions like the playground, research, and many more. Doing data analysis and machine learning for several years. The Competition is sponsored by the Competition Sponsor listed above and hosted on the Sponsor's behalf by Kaggle Inc ('Kaggle'). Look for clean datasets because you don't want to waste time cleaning the data yourself. Join us to compete, collaborate, learn, and do your data science work. Lisboa, The value of personalised recommender systems to e-business: a case study, Proceedings of the 2008 ACM conference on Recommender systems. Kaggle Ensembling Guide - Free download as PDF File (. So if you are playing with the data set of an archived competition, you would be able to submit your predictions but you won't be ranked. Most python packages like NumPy, Pandas or Sklearn can be installed manually with pip – python installer. WriteXmlSchema method to create new. Kaggle Learn is "Faster Data Science Education," featuring micro-courses covering an array of data skills for immediate application. We can run our projects on Google Colab instances with couple of manual steps, allowing us to automate our dependency setup, source and datasets download and remote Terminal, Jupyter, Tensorboard, Serving access. Participants in a laboratory experiment solve a real task, first under a noncompetitive piece rate and then a competitive tournament incentive scheme. I carefully read the Kaggle indications, studied the datasets, and decided to go about it one step at a time. we ran competitions with Kaggle, but now we are crowdsourcing ourselves as we'd rather own and curate our own solver-crowd. In this video, Kaggle data scientist Rachael walks you through setting up your GCP account (no credit card required!) and uploading you own data as a BigQuery dataset from a Kaggle Kernel. The most significant learning for me has been the ability to understand a dataset and then devise a framework of the data science solution. The competition lasted three months and ended a few weeks ago. There are competitions going on the site which help beginner data scientists to show their skills and get hired by MNCs. Cannot download large datasets over the kaggle API how to list completed competitions with kaggle API? #209 opened Aug 20, 2019 by appleyuchi. Kaggle is a platform for predictive modeling and analytics competitions. Beta release - Kaggle reserves the right to modify the API functionality currently offered. I don't regret anything I've done. However, the preferred option is to use Anaconda. • Usual tasks include: – Predict topic or sentiment from text. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Marketing and Econ. Dataset is pulled in from the Kaggle competition for San Francisco crime data. Google-Landmarks: A New Dataset and Challenge for Landmark Recognition The Kaggle competition data doesn't seem to contain the actual photos, just links. He is the Head of Energy Forecasting at SAS Institute Inc. This guide will. To this day, the 0. In some of our simpler competitions, 1,000 to 2,000 people will submit. This data set contains the annotations for 5171 faces in a set of 2845 images taken from the Faces in the Wild data set. Insurance ownership data: The 2000 CoIL Challenge was to predict whether customers would purchase caravan insurance. !kaggle datasets list Others information like size of the dataset and download count is also available in the details. So here are some excellent Kernels for EDA / Data Exploration using R 1. Kaggle competition. XPRIZE creates incentive competitions to entice the crowd to take action, and bring us closer to a world of Abundance. The algorithms can either be applied directly to a dataset or called from your own Java code. About the Data. Join LIPS INDIA for comprehensive Digital Marketing course in Mumbai with Hands-on Implementation and Practical Training. Instead, just download “train. Google Cloud Platform Overview More Samples & Tutorials. The first step is to download the dataset. The goal of the contest was to promote research on real-world link prediction, and the dataset was a graph obtained by crawling the popular Flickr social photo sharing website, with user identities scrubbed. com, accessible using a command line tool implemented in Python 3. Almost all datasets are freely available for download today. One of its applications is in the prediction of house prices, which is the putative goal of this project, using data from a Kaggle competition. Nielsen Datasets. Jumpshot shows you unprecedented detail into brand and retailer performance across the ecommerce market. xsd schema file and class file for the languages C#, VB, JScript, and Visual J#. Marketing and Econ. Kaggle will partner with organisations to host up to five pro-bono research competitions a year, and they are asked to submit a brief proposal for consideration. We develop a computational framework for predicting business performance that takes into account both intrinsic (e. Kaggle competition. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home. These datasets are available for download and can be used to create your own recommender systems. 10 R Packages to Win Kaggle Competitions by Xavier Conort Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. json" with my API credentials. International football competition contested by the women's national teams recognised by the Asian Football Conferation (AFC). From a learning perspective, this makes a great deal of sense, and the elements of play and competition add layers of motivation and excitement. And of course all the authors of Vowpal Wabbit, by name its principal developer: John Langford. Environment and file descriptions 0. CIFAR-10 dataset. Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Noncommercial-Share Alike 3. AWS Digital Customer Experience Competency Partners support all phases of the digital customer acquisition and retention life cycle including: content management and marketing automation to engage prospects and customers with the right experience, effective and secure commerce solutions to create seamless buying experiences, and data analytics solutions to support your decisions and retain. What should you do? Update your dataset, of course! This short video will show up how to. Social Network Dataset Finders. Until now, we used a dataset of 891 passengers for whom we know if they survived or not. Dataset consisted of details of customers of bank and campaing strategies based on which their term deposit subscriptions is to be predicted. Project completed in the course of Machine Learning Engineer Nanodegree - Explore data and Observe features - Train and Test models. The golden questions and allocation tool for our consumer segmentation are also available upon request. About this Dataset A first estimate of retail sales in value and volume terms for Great Britain, seasonally and non-seasonally adjusted. This dataset is also available as a builtin dataset in keras. ) Plant Images: A SAMPLE OF IMAGE DATABASES USED FREQUENTLY IN DEEP LEARNING: A. Lots of fun in here! KONECT - The Koblenz Network Collection. Available in PRO Platform™ Download all Reports & Infographics from PRO Platform™. Abstract: The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. I’ll walk you through two competitions that dealt with spam, and tell you how I won them. Springleaf Marketing Response | Kaggle 3. There are online repositories of datasets that are specifically curated for machine learning. Tableau Public is free software that can allow anyone to connect to a spreadsheet or file and create interactive data visualizations for the web. Then the dataset was split as 80 percent train and 20. Kaggle’s platform is the fastest way to get started on a new data science project. Flexible Data Ingestion. Normalised values are provided too. Kaggle competitions encourage you to squeeze out every last drop of performance, while typical data science encourages efficiency and maximizing business impact. Download and place the dataset of this competition as below. Today we’re pleased to announce a 20x increase to the size limit of datasets you can share on Kaggle Datasets for free! At Kaggle, we’ve seen time and again how open, high quality datasets are the catalysts for scientific progress–and we’re striving to make it easier for anyone in the world to contribute and collaborate with data. Those datasets are generally cleaned up in advance so that you can test algorithms swiftly. Caltech Silhouettes: 28×28 binary images contains silhouettes of the Caltech 101 dataset; STL-10 dataset is an image recognition dataset for developing unsupervised feature learning, deep learning, self-taught learning algorithms. However, datasets developed by for-profit companies may be available for a fee. The world's largest community of data scientists. Along with hosting Competitions (it has hosted about 300 of them now), Kaggle also hosts these 3 very important things: Datasets, even the ones not related to any competition: It houses 9500 + datasets as compared to just the 300 competitions (at the time of writing). This list does not represent the amount of time left to enter or the level of difficulty associated with posted datasets. Dhanurjay Patil, the Chief Data Scientist at the White House's Office of. This guide will. Companies provide datasets and descriptions of the problems on Kaggle. `Hedonic prices and the demand for clean air', J. As part of the FGVC5 workshop at CVPR 2018 we are conducting the iNaturalist 2018 large scale species classification competition. This was what I had seen in a Kaggle competition, the forest cover one, and wanted to see if my results there were reproducible with any other data. Kaggle is a platform for predictive modeling and analytics competitions. The official Kaggle Datasets handle. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Since MNIST restricts us to 10. I am now publishing my code (esp notebooks. In this section I will share with you my experience in downloading dataset from Kaggle and other. Data sets are made available to approved academics for classroom use, dissertations and/or other research and are free of charge to members of the Marketing EDGE Professors' Academy. Below you can find a list of benchmark MTR datasets that we have collected along with the corresponding sources and citations. From the audience, Claudia Perlich pointed out that she won data mining competitions on breast cancer, movie reviews, and customer behavior without any prior knowledge. They can also be used to compete in Kaggle competitions and complete the kaggle learning courses. Build with our huge repository of free code and data. Active 8 months ago. Throughout this guide, you’ll see important pros and cons for three of the top marketing automation systems: HubSpot, Marketo, and Pardot. Our experiments on synthetic and real datasets demonstrated superiority of a hybrid prediction model that adopts both link-based and context-based assumptions. See the complete profile on LinkedIn and discover Zhehan's. I’d like to thank Kaggle for hosting the competition and Criteo for sharing this amazing dataset. It focuses around sharing datasets as well as machine learning competitions. If you've ever been curious about learning machine learning but overwhelmed by the wealth of information out there, you've come to the right post. The goal was to predict success or failure of a grant application based on information about the grant and the associated investigators. You can find all kinds of niche datasets in its master list, from ramen ratings to basketball data to and even Seattle pet licenses. If you are interested in testing your algorithms on weed images 'from the wild' with no artificial lighting, you can find some samples at:. The 4 th NYCDSA class project requires students to work as a team and finish a Kaggle competition. The FDA launched openFDA, which will allow developers to access public FDA data through open APIs, raw data downloads, and documentation and examples. The page offers more than 500 datasets, challenging data competitions and many other features. Dataset: With the help of WWF, a third-party company (MakerCollider) collected more than 8,000 Amur tiger video clips of 92 individuals from ~10 zoos in China. Machine Learning for Predicting Bad Loans It's a real world data set with a nice mix of categorical and continuous variables. com BigML is working hard to support a wide range of browsers. Winning this competition introductory words for essays is the highest honor that a doctoral student can receive from SCP, the premier society for researchers in …. Sizes of Data provided in recent competitions on Kaggle are running above 1 GB. Trained a Deep Neural Network on GPU to identify whether two questions have similar context (if two questions ask for the same information). The dataset is a csv containing 30k highly upvoted top-level comments made in /r/science between January 2017 and June 2018. 6, pytorch1. Here are some amazing marketing and sales challenges in Kaggle that allows you to work with close to real data and find out for yourself how you can make the most of analytics in marketing and sales. This challenge was to predict the number of votes, comments, and views that issues created on See Click Fix would get. The Kaggle Titanic Survivors competition is the one any Kaggle newcomer should start with, as it’s always open (leaderboard periodically cleans up), straightforward to follow. The algorithms can either be applied directly to a dataset or called from your own Java code. 1Geographics 7. List of Free available DATA SETS for data Analysis Kaggle - Kaggle is a site that hosts data mining competitions. Stumped? Ask the friendly Kaggle community for help. However, uploading other datasets might be tiresome. There are active ones and there are archived ones. If you've ever been curious about learning machine learning but overwhelmed by the wealth of information out there, you've come to the right post. Telstra Network Disruptions (TND) Competition ended on 29th February 2016. This is a fairly straightforward competition with a reasonable sized dataset (which can’t be said for all of the competitions) which means we can compete entirely using Kaggle’s kernels. Kaggle: Kaggle is in the business of growing data scientists. There I develop my data scientist skills in order to become a highly qualified data scientist. 1) Train Dataset. Google BigQuery has pure separation of storage and compute, which allows for Public Datasets [0] to exist in ready-to-query highly optimized format. It turns out that humans, dogs and cats have no problem with this classification task, but computers find it more difficult. If you have any questions regarding the challenge, feel free to contact [email protected] Kaggle datasets into jupyter notebook. Upload station. Run kaggle datasets create -p /path/to/dataset to create the dataset Your dataset will be private by default. Kaggle, a Google-owned community for AI researchers and developers that offers tools which help to find, build, and publish datasets and models, is integrating with Google’s Data Studio. Everyone wants to better understand their customers. Kaggle is a site where people create algorithms and compete against machine learning practitioners around the world. Charts, Data and Research for Marketers. csv and trip. This section contains several examples of how to build models with Ludwig for a variety of tasks. Computers love numbers, but not text, so the next step was to transform the tweet into a matrix representation. Now, 10k of those comments were removed by moderators, so to recover the text I used the pushshift. Kaggle Competitions Master Kaggle May 2019 - Present 7 months. We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. However i was facing issues by using the request method and the downloaded output. Download Retail Sales. target Split dataset. Machine Learning Enthusiasts, aspiring data scientists, as well as professionals in the field come together in. Join us to compete, collaborate, learn, and do your data science work. Exploring and reading other Kagglers’ code is a great way to both learn new techniques and stay involved in the community. By adjusting the search results to the user's previous activities and leveraging friends as a trust filter, the search results are relevant, personalized, and fraud-resilient. Data Science Skills Poll Results: Which Data Science Skills are core and which are hot/emerging ones? Annual Software Poll Results: Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis. Datasets - Cars - World and regional statistics, national data, maps, rankings. Download and place the dataset of this competition as below. In addition to annotating videos, we would like to temporally localize the entities in the videos, i. Downloads & Licenses is interest and what their ideas are around Kaggle competitions and datasets and using Alteryx. The impacts of weather and climate are felt by every industry, every day. can download dataset on your computer by. 5M messages. I initially worked on a project where I used SQL, Python, and Azure ML Studio to assign missing identifiers in a database by cross referencing another database, in order to maintain the integrity and consistency of data. Kaggle is an online Data Science community which hosts competitions. Competition Begins April 24 2019. Just for the ones who has yet to come accross; "Kaggle is a platform for predictive modelling and analytics competitions on which companies and researchers post their data and statisticians and data miners from all over the world compete to produce the best models. You’d probably need to register a Kaggle account to do that. Under Kaggle's "Competition" tab there are many competitions that you can join. Hexagon-ML obtains this award for: Pioneering a new type of competition, the Reinforcement Learning Competition, and implementing it under a novel computational environment for KDD Cup 2019. It will also be included in the first of Kaggle's new monthly blog series "Dataset of the Week" as well as the. First, we download data from Kaggle competition page. Fortunately, there is Meta Kaggle dataset, which contains various data on competitions, users, submissions, and kernels. We’ve been improving data. Kaggle is a community and site for hosting machine learning competitions. Thank you for asking me this question. However, the preferred option is to use Anaconda. This significantly. , Rinzivillo, S. One key feature of Kaggle is “Competitions”, which offers users the ability to practice on real-world data and to test their skills with, and against, an international community. keerth516 6-Nov-13 6:19am. Columns in the submission file: Id, Solution. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. Coupling Kaggle's excellent marketing with their competition setup leads many people to believe that data science is all about fitting models. This tutorial is based on part. Vectorize and split dataset. A ‘\N’ is used to denote that a particular field is missing or null for that title/name. Jun 15, 2017: Taster challenges with amazon bin image dataset will not be held. Some of them are listed below. Upload station. platform (owned by Google LLC), which provides access to datasets, a discussion forum for participants, the repository of submitted results and a. Microsoft’s 2015 malware classification competition on Kaggle was a huge success, with the dataset provided by Microsoft cited in more than 50 research papers in multiple languages. Customer Support on Twitter: This dataset on Kaggle includes over 3 million tweets and replies from the biggest brands on Twitter. There are so many resources available out there. Of course entirely the same framework can be applied to other general and usual datasets - including Kaggle competitions. T analysis 5. Download and place the dataset of this competition as below. 0, you can refer to requriements. Alexis Sanders shares her own guide on how to learn machine learning, detailing the pros and cons through the viewpoint of a beginner. Look for datasets without too many rows and columns, because those are easier to work with. Download the dataset directly to Google Drive via Google Colab. I automated many components of the machine learning workflow to improve my efficiency while working on Kaggle competitions. By building the model, you will. This is just like the “Datasets” tab, where you can click on the competition and download the data for your models. まず、Kaggle上のAccountを作成してSign inする必要が有ります。ここからKaggle Accountを作成します。GoogleやFacebookなどのAccountでSocial loginさせる事も可能です。 参加したいCompetitionを決めDataset等をDownloadする. You also have the opportunity to create new features to im. and Giannotti, F. In addition, we also use datasets from Kaggle Competitions, because the public leaderboards on Kaggle allow students to test their models against the best in the world (the Kaggle datasets are not listed here). But the problem is in. This competition focused on developing text mining algorithms for document classification. Some examples of this include data on tweets from Twitter and stock price data. Kaggle hosts certain in Class contests that are free to join for everyone. Our experiments on synthetic and real datasets demonstrated superiority of a hybrid prediction model that adopts both link-based and context-based assumptions. Any Kaggle user can then create a new script or notebook, enabling them to run R, Python, Julia, and potentially SQLite code on the data without a download. Available in PRO Platform™ Download all Reports & Infographics from PRO Platform™. The official Kaggle Datasets handle. Feigelson & G. The Nielsen datasets at the Kilts Center for Marketing is a relationship between the University of Chicago Booth School of Business and the Nielsen Company and makes comprehensive marketing datasets available to academic researchers around the world. We can use this dataset to find out: of dataset downloads. Join us to compete, collaborate, learn, and do your data science work. I believe that such competitions help to improve the unique data analysis skills. The Kaggle Titanic Survivors competition is the one any Kaggle newcomer should start with, as it’s always open (leaderboard periodically cleans up), straightforward to follow. A user can find any kind datasets and download it easily like just one click. Recognizing the intricate relationships between the many areas of business activity, JBR examines a wide variety of business decisions, processes and activities within the actual business setting. can download dataset on your computer by. The competitors will download the DDC dataset, which. Flexible Data Ingestion. Free online access to data sets is available for Members of the Marketing EDGE Professors' Academy. A large number of studies has been canvassed by the growing rates of diffusion of Open Source Software. Look for clean datasets because you don't want to waste time cleaning the data yourself. What the Kaggle acquisition by Google means for crowdsourcing. • The order of words is ignored or lost and thus important information lost. This unified scheme should allow for appropriate preliminary comparisons and the creation of the pre-conference proceedings. com and barnesandnoble. Relevant Papers: N/A. You will build a regression model based on a data set that is publicly available in Kaggle, a large community site of data scientists that compete against each other to solve data science problems. 1%) meniscal tears; labels were obtained through manual extraction from clinical reports. The goal was to predict success or failure of a grant application based on information about the grant and the associated investigators. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. There I develop my data scientist skills in order to become a highly qualified data scientist. -o, --force Skip check whether local version of file is up to date, force file download -q, --quiet Suppress printing information about the upload/download progress Examples: kaggle datasets download zillow/zecon. We have kept the page as it seems to still be usefull (if you know any database or if you want us to add a link to data you are distributing on the Internet, send us an email at arno sccn. input ├── train_images/ ├── test_images/ └── train. g beginners competitions can be listed using!kaggle competitions list — category. If using JSON-LD, this is represented using JSON list syntax. Competition Use. Feel free to fork the code to adapt for your own needs. Which state had the most awards? (Using sort () on your table is useful here. More details can be found in the technical report below. Registered users can choose among 13,321 high-quality themed datasets. This guide will. Flexible Data Ingestion. Success in Kaggle is a combination of many things like Machine Learning experience, type of competitions and your ability to work in a team. One of its applications is in the prediction of house prices, which is the putative goal of this project, using data from a Kaggle competition. Grant application data: These data origin ated in a Kaggle competition. Machine Learning with Spark: Kaggle's Driver Telematics Competition For computations on the entire data set we used a comSysto cluster with 3 nodes at 8 cores (i7) and 16GB RAM each. Dataset Gallery: Media, Marketing & Advertising | BigML. Beta release - Kaggle reserves the right to modify the API functionality currently offered. Don't show this message again. Those data are just samples by which people who are trying to get into data science field with no prior knowledge or experience can understand what is exactly used and how the data sets should be analysed. If you’re learning data science, you're probably on the lookout for cool data science projects. Additionally, looking at some of the other cross classification dependencies - such as cabin class and. Kaggle is the world's largest community of data scientists. In this post, you will discover a simple 4-step process to get started and get good at competitive. Follow us on twitter for helpful resources and interesting competitions. Spark is designed for Big Data processing. csv” file of predictions to Kaggle for the first time. Download the dataset directly to Google Drive via Google Colab. 38 Feature Extraction: Hidden Features • Sometimes there has some information leakage in the dataset provided by Kaggle competition • Timestamp information of data files • Some incautiously left meta-data inside HTML or text • May lead to unfair results, so normally I skip this kind of competitions! 39. Flexible Data Ingestion. Join us to compete, collaborate, learn, and share your work. Source: N/A. Machine learning is a branch in computer science that studies the design of algorithms that can learn. Leave the Location set to Global. Contribute to bestfitting/kaggle development by creating an account on GitHub. Browsing Kaggle datasets: This command will list the datasets available in kaggle. 7-months into being a machine learning engineer, I finally entered my first Kaggle competition. Will delete the zip file when completed. 5M messages. Since then, we’ve been flooded with lists and lists of datasets. Participate or launch new competition for students, scientists and programmers. Lyft Level 5 dataset sample. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: