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Kaggle open challenges

We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. Got it. Learn more. Competitions Grow your data science skills by competing in our exciting competitions. Find help in the documentation or learn about InClass competitions. add Host a Competition. We use cookies on Kaggle to deliver. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. Got it. Learn more. 9238. Dataset. COVID-19 Open Research Dataset Challenge (CORD-19) An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House. Allen Institute For AI and 8 collaborators • updated 12 days ago (Version. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. Got it. Learn more. 9244. Dataset. COVID-19 Open Research Dataset Challenge (CORD-19) An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House. Allen Institute For AI and 8 collaborators • updated a day ago (Version 83.

Kaggle Competition

  1. An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White Hous
  2. On March 17 2020, by the start of COVID-19 lockdown around the globe, Kaggle announced COVID-19 Open Research Dataset Challenge (CORD-19) competition in collaboration with the Allen Institute for AI in partnership with the Chan Zuckerberg Initiative, Georgetown University's Centre for Security and Emerging Technology, Microsoft Research, IBM, and the National Library of Medicine — National Institutes of Health, in coordination with The White House Office of Science and Technology Policy
  3. While Kaggle is a well-known platform for Data Science competitions, The data science challenge platform AIcrowd hosts multiple open data science challenges each year. The challenges cover image classification problems, text recognition, reinforcement learning, adversarial attacks, image segmentation, resource allocation optimization, and many other areas across multiple domains. They were.
  4. Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access free GPUs and a huge repository of community published data & code. Register with Google . Register with Email. Inside Kaggle you'll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time. list Maintained by.
  5. One way to categorise the challenges in Kaggle is based on the format and shape of the data which is going to be used for the competition. In general, you could classify the competitions based on..

In recent years, many top participants make a write-up describing their solution and even open their code after the competition. This is a great initiative. However, the short write-up is usually insufficient to reproduce the results and Kaggle-style code is usually somewhat messy and hard to understand without comments. During the challenge, everybody is chasing the leaderboard in a hurry and. There's a new $20,000 challenge on Kaggle that uses a dataset titled The Abstraction and Reasoning Corpus. The aim of this episode is to get you up to spee.. The Open Source Imaging Consortium (OSIC) was proud to partner with Kaggle to host the first ever computational challenge for interstitial lung diseases: The OSIC Pulmonary Fibrosis Progression Challenge. A $55,000 prize was awarded to the Kaggle investigator (s) who devised the highest performing algorithm Neural Networks from Scratch: https://nnfs.ioChannel membership: https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ/joinDiscord: https://discord.gg/sen..

  1. As part of the Google company, Kaggle is best known for organizing various machine learning and data science challenges, including the current one — COVID-19 Open Research Dataset Challenge, or simply CORD-19 Challenge. The CORD-19 dataset consists over 29,000 articles, among which 13,000 have full text
  2. Join me as I attempt a Kaggle challenge live! In this stream, i'm going to be attempting the NYC Taxi Duration prediction challenge. I'll by using a combinat..
  3. Kaggle is a well-known community website for data scientists to compete in machine learning challenges. Competitive machine learning can be a great way to hone your skills, as well as demonstrat
  4. The challenge is based on the V5 release of the Open Images dataset. The images of the dataset are very varied and often contain complex scenes with several objects (explore the dataset). This year the Challenge will be again hosted by our partners at Kaggle. The challenge has three tracks
  5. The 2018 and 2019 editions of the challenge were run by Google AI in partnership with Kaggle. The results are available here: Open Image Challenge 2019; Open Image Challenge 2018 ; The evaluation servers of the 2019 challenge are still accessible. This enables evaluating new methods on the hidden challenge dataset and to compare properly to previous results. Please check the Train data and.
  6. The images are very varied and often contain complex scenes with several objects (7 per image on average; explore the dataset). The Open Images Challenge offers a broader range of object classes than previous challenges, including new objects such as fedora and snowman. The Challenge is hosted by Kaggle. The challenge has two tracks

Submitted Solution for Kaggle COVID-19 Open Research

Kaggle_Challenges. Kaggle based machine learning challenges. Completed. Titanic_Survival - solution using Random Forest algorithm. Walmart_Trip_Type_Classification - solution using Classification algorithm. Walmart_Trip_Type - Solution using clustering algorith Show off your BigQuery ML and Kaggle skills: Competition open now HOLLAND, Mich., Monday, December 14, 2020 - The Open Source Imaging Consortium (OSIC) announced today the winners of its $55,000 OSIC Pulmonary Fibrosis Progression Challenge, the first-ever computational challenge for interstitial lung diseases (ILDs).The AI-focused competition was administered by Kaggle, the world's largest data science community platform, and asked participants to use.

Kaggle: COVID-19 Open Research Dataset Challenge (CORD-19) Kaggle has issued a call to action to the world's artificial intelligence experts to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions. Post author By limsub. Post date. April 17, 2020 As a response to the COVID-19 crisis, Kaggle is hosting a challenge sponsored by AI2, CZI, MSR, Georgetown, NIH & The White House . The dataset is a corpus of around 30 000 scientific articles related to the virus. The challenge is organised around tasks that are stated as What is known about transmission, incubation, and environmental stability? for instance. Every task is explained with a small text detailing what information is needed

Selection of some interesting Kaggle Kernels. Contribute to pierpaolo28/Kaggle-Challenges development by creating an account on GitHub Mar 27, 2018 · 6 min read Kaggle the biggest data science platform just launched a 5-day challenge on data cleaning for beginners in data science Awesome Open Source. Combined Topics. kaggle-competition x. Advertising 10. All Projects. Application Programming Interfaces 124. Applications 192. Artificial Intelligence 78. Blockchain 73. Build Tools 113. Cloud Computing 80. Code Quality 28. Collaboration 32. Command Line Interface 49. Community 83. Companies 60. Compilers 63. Awesome Open Source. Combined Topics. kaggle x. Advertising 10. All Projects. Application Programming Interfaces 124. Applications 192. Artificial Intelligence 78. Blockchain 73. Build Tools 113. Cloud Computing 80. Code Quality 28. Collaboration 32. Command Line Interface 49. Community 83. Companies 60. Compilers 63. Computer. Kaggle Airbus Ship Detection Challenge. I implemented Oriented SSD for the kaggle competition Airbus Ship Detection Challenge. Example. References. Learning a Rotation Invariant Detector with Rotatable Bounding Box arXiv; Multiscale Rotated Bounding Box-Based Deep Learning Method for Detecting Ship Targets in Remote Sensing Images mdpi.com; Acknowledgemen

The Top 104 Kaggle Open Source Projects. Categories > Companies > Kaggle. Data Science Ipython Notebooks ⭐ 20,187. Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines The Top 104 Kaggle Open Source Projects. Categories > Companies > Kaggle. Data Science Ipython Notebooks ⭐ 20,321. Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines

Kaggle — Learn Python Challenge: Day 5. Editor: Ishmael Njie . DataRegressed Team. Follow. Jun 16, 2018 · 3 min read. Day 5 is here! Here are the links to the previous exercises: Day 1. 3 Kaggle alternatives for collaborative data science If you're dismayed that Kaggle is now part of the Alphabet soup, these sites continue the tradition of crafting a bounty-paying, competitive. Kaggle Open Images Challenge 2019で3位を獲得しました. Yusuke Niitani. Engineer. Kaggle Open Images Challenge 2019で3位を獲得しました。. h ttps://www.kaggle.com/c/open-images-2019-instance-segmentation/leaderboard. Index Kaggle Carvana Image Masking Challenge solution with Keras. This solution was based on Heng CherKeng's code for PyTorch. I kindly thank him for sharing his work. 128x128, 256x256, 512x512 and 1024x1024 U-nets are implemented. Public LB scores for each U-net are

A computer vision challenge was hosted at kaggle.com about a year ago named IEEE's Signal Processing Society — Camera Model Identification. The task was to assign what type of camera was used to capture an image. After the competition was over This is an open solution to the Airbus Ship Detection Challenge. In this open source solution you will find references to the neptune.ml. It is free platform for community Users, which we use daily to keep track of our experiments. Please note that using neptune.ml is not necessary to proceed with this solution. You may run it as plain Python script . data-science machine-learning deep.

Top AI Competitions and Challenges in 2021 Apart From Kaggl

  1. kaggle-hpa-image-classification. Code for 3rd place solution in Kaggle Human Protein Atlas Image Classification Challenge. To read the detailed solution, please, refer to the Kaggle post. Hardware. The following specs were used to create the original solution. Ubuntu 16.04 LTS; Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz; 3x NVIDIA TitanX.
  2. Riiid's AIEd Challenge attracted 3,395 teams from 90 countries, the most of any 2020 Kaggle algorithm competition hosted by a business entity. Among the participants in those teams were 52 of Kaggle's 270 Grandmasters, the highest rank for Kaggle competitors based on past performance. In comparison, 2020 competitions averaged 25 Grandmasters. Furthermore, 20 of the top 100 Kaggle ranked competitors participated in the AIEd challenge
  3. kaggle-Toxic-Comment-Classification-Challenge. https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge. Steps to reproduce (RNN + CNN + bert) Download the dataset from Kaggle and put it in data/ Tensorflow 1.13.2, Keras 2.2.4; run toxic-data-preprocessing.py (data preprocessing) run version5_*.ipynb (MultiBiGRU models
  4. A more detailed definition of the of the competition is provided on the Kaggle RSNA Pneumonia Detection Challenge website: https://www.kaggle.com/c/rsna-pneumonia-detection-challenge
  5. Kaggle is a global online competition platform made up of data scientists and machine learning practitioners designed to allow users to publish data and create data science challenges. With well over 5,000,000 registered users from 250 different countries, Kaggle competitions have resulted in many successful programs including advancing medical research in HIV and cancer, as well as creating forecasting models for traffic and driving advances in neural networks
  6. Kaggle just held the Google AI Open Images - Object Detection Track competition from July 4 to August 30. I particiated, and finished at the 86th spot (bronze zone). I was disappointed with this result. But anyway I'd like to share how I approached the competition and what I've learned from it. The Kaggle Google AI Open Images - Object Detection Track competition was quite.

Join Kaggle experts, Tarun Paparaju, Ruchi Bhatia and Paras Varshney as we dive into ways you can up-level your Data Science workflow with Z by HP and NVIDIA - helping you crush that next competition challenge. AI & Deep Learning. Sub brand NVIDIA WEBINAR. Real-World Applications to Kaggle's Most Challenging Problems. Introduction Date: 10 December 2020 Time: 3:00pm - 4:00pm IST Duration. New to Kaggle? Our Titanic competition is a great place to start. In this video, Kaggle data scientist Dr. Rachael Tatman walks you through the Titanic compe..

The challenge banner. Over the last three months, I have participated in the Airbus Ship Detection Kaggle challenge. As evident from the title, it is a detection computer vision (segmentation to be more precise) competition proposed by Airbus (its satellite data division) that consists in detecting ships in satellite images.Before I start this challenge, I was (and somehow still) a beginner in. Keras-RetinaNet for Open Images Challenge 2018. This code was used to get 15th place in Kaggle Google AI Open Images - Object Detection Track competition: https://www.kaggle.com/c/google-ai-open-images-object-detection-track/leaderboard. Repository contains the following: Pre-trained models (with ResNet101 and ResNet152 backbones Details: On March 17 2020, by the start of COVID-19 lockdown around the globe, Kaggle announced COVID-19 Open Research Dataset Challenge (CORD-19) competition in collaboration with the Allen Institute for AI in partnership with the Chan Zuckerberg Initiative, Georgetown University's Centre for Security and Emerging Technology, Microsoft Research, IBM, and the National Library of Medicine — National Institutes of Health, in coordination with The White House Office of Science and. Deepfake Detection Challenge. Solution for the Deepfake Detection Challenge. Private LB score: 0.43452. Solution description Summary. Our solution consists of three EfficientNet-B7 models (we used the Noisy Student pre-trained weights). We did not use external data, except for pre-trained weights. One model runs on frame sequences (a 3D.

Fraud detection Kaggle challenge. Figure 1. Banner image from the IEEE CIS Fraud Detection Challenge. In this challenge, IEEE partnered with the world's leading payment service company, Vesta Corporation, in seeking the best solutions for fraud prevention. Successful ML models improve the efficacy of fraudulent transaction alerts, helping hundreds of thousands of businesses reduce fraud loss. The new Santa Kaggle Challenge. This year is a special year for me in that challenge. Normally I try to compete with all my time I have and get the best possible score I can achieve and maybe blog about it when it is all over. But this year I blog about it while competing. I think it is more interesting for people to read the results in between instead of just the polished end result. I know. I would be also very interesting to know if there are other sites/challenges apart from Kaggle! - Open the way Oct 31 '12 at 12:10. Are you asking whether academics submit data to Kaggle or whether they take part in Kaggle competitions? - eykanal ♦ Oct 31 '12 at 13:14. 3. On a related note, this seems too discussion-oriented to me. The word opinions in the title tends to give it away. Kaggle's CEO, Anthony Goldbloom, shared his perspective on the DFDC: Kaggle is thrilled to be collaborating with Facebook on this challenge. AI has made dramatic leaps forward over the last decade thanks to open datasets and open challenges. This challenge is a powerful step in tackling one of the most difficult open issues in AI today

Kaggle Challenge : Ad Tracking fraud detection pour TalkingData Découvrez le retour d'expérience de Hao Chen suite à son premier Kaggle Challenge. Par Hao Chen Data Scientist. 31/05/2018 . J'ai écrit cet article suite à ma participation à mon premier challenge Kaggle - TalkingData Ad Tracking Fraud Detection Challenge - pour partager avec vous les apprentissages que j'en ai. Kaggle is the global home of machine learning competitions, open datasets and data science collaboration. Having hosted many high-profile competitions and recently crossing a million users whil The Most Comprehensive List of Kaggle Solutions and Ideas. This is a list of almost all available solutions and ideas shared by top performers in the past Kaggle competitions. This list will get updated as soon as a new competition finished. If you find a solution besides the ones listed here, I would encourage you to contribute to this repo by making a pull request. The symbols were used in.

Kaggle: Your Machine Learning and Data Science Communit

Assystem participates in Kaggle challenge COVID-19 Open Research Dataset (CORD-19) to develop text and data mining tools that can help the medical community developing answers to high priority scientific questions. In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). This freely available. Caused by the novel coronavirus (i.e., SARS-CoV-2), the coronavirus disease 2019, commonly abbreviated as COVID-19, has become a pandemic in the last 3 months by spreading to over a hundred o

How to win a Data Science challenge in Kaggle? by Hassan

  1. Kaggle Challenge: TalkingData AdTracking Fraud Detection TalkingData, China's largest independent big data service platform, covers over 70% of active mobile devices nationwide. Their current approach to prevent click fraud for app developers is to measure the journey of a user's click across their portfolio, and flag IP addresses who produce lots of clicks, but never end up installing apps
  2. Open Source Imaging Consortium against interstitial lung disease. Our Goals Kaggle Challenge Membership Working Groups Press Blog Open Source Imaging Consortium (OSIC) OSIC is a co-operative effort between academia, industry and philanthropy designed to enable rapid advances in the fight against Idiopathic Pulmonary Fibrosis (IPF), fibrosing interstitial lung diseases (ILDs) and other.
  3. Challenges. Here is an overview of all challenges that have been organised within the area of medical image analysis that we are aware of. Please contact us if you want to advertise your challenge or know of any study that would fit in this overview. Filter Challenges Title or Description Modality Anatomical Structure Anatomical Region Organization Challenge Series Task Type Educational 248.
  4. Open notebook settings. lesson-3-rsna-pneumonia-detection-challenge-kaggle_ Rename. File . Edit . View . Insert . Runtime . Tools . Help . Share. Share notebook. Open settings. Sign in. Code Insert code cell below. Ctrl+M B. Text Add text cell. Copy to Drive Connect Click to connect. Additional connection options Editing. Toggle header visibility. Intro to deep learning for medical imaging by.
  5. Open Images Challenge 2019 In conjunction with this release, we are also introducing the second Open Images Challenge, 2019 by Kaggle. The evaluation servers will open on June 3rd for the object detection and visual relationship tracks, and on July 1st for the instance segmentation track. The deadline for submission of results is October 1st, 2019. We hope that the exceptionally large and.

Overview Downloads Evaluation Past challenge: 2019 Past challenge: 2018 News Extras Extended Download Description Explore ☰ The annotated data available for the participants is part of the Open Images V5 train and validation sets (reduced to the subset of classes covered in the Challenge) 2018 Kaggle ML & DS Survey Challenge. Some time ago Kaggle launched a big online survey for kagglers and now this data is public. There were multiple choice questions and some forms for open answers. Survey received 23k+ respondents from 147 countries. As a result we have a big dataset with rich information on data scientists using Kaggle. In this kernel I compare DS in USA, Russia, India and. In today's blog post, I interview David Austin, who, with his teammate, Weimin Wang, took home 1st place (and $25,000) in Kaggle's Iceberg Classifier Challenge.. David and Weimin's winning solution can be practically used to allow safer navigation for ships and boats across hazardous waters, resulting in less damages to ships and cargo, and most importantly, reduce accidents, injuries. Solving our global challenges through turning ocean data into innovation opportunities for the digital blue economy. Our mission. The mission of ODF Sweden is to enable data-driven innovation by both commercial and non-commercial actors to ensure that the ocean and its resources are managed in the best possible and most sustainable way. In doing so, one of ODF Sweden's goals is to enable. During my undergraduate internship in 2015 I started a side project called OpenBikes. The idea was to visualize and analyze bike sharing over multiple cities. Axel Bellec joined me and in 2016 we won a national open data competition. Since then we haven't pursued anything major, instead we use OpenBikes to try out technologies and to apply concepts we learn at university and online

Kaggle. 63,828 likes · 124 talking about this. The world's largest community of data scientists. Join us to compete, collaborate, learn, and share your work Kaggle. 63,806 likes · 114 talking about this. The world's largest community of data scientists. Join us to compete, collaborate, learn, and share your work 349. Categorical Feature Encoding Challenge. Binary classification, with every feature a categorical. Prize: Swag. Team: 1,342. Kind: Playground. Year: 2019. 1st place; 2nd place; 3rd place; 4th place; 348. 2019 Kaggle ML & DS Survey. The most comprehensive dataset available on the state of ML and data science. Prize: $30,000. Team: - Kind: Analytics. Year: 2019. 1st plac Kaggle, a web-based information sharing site and public arena for data scientists competing to prove they're the smartest of the smart, has initiated new challenges designed to advance machine learning-based analysis and access into more than 44,000 scholarly articles about COVID-19 and related coronavirus problems. Called the COVID-19 Open Research Dataset Challenge (CORD-19), it comes in the.

Writing papers/tech reports after Kaggle competitions by

One of the biggest challenges of this competition is how to combine multiple hypotheses in order to produce only 3 required for the evaluation. Obviously, it is beneficial to select 3 very diverse proposals as it increases the chance that one of them will be close to the Ground Truth Dataset Challenge on Kaggle. The outline follows these five steps: 1.register on the Kaggle website, 2.acquire the training data, 3.write a Python script that computes song popularity, 4.create and verify the solution file, and 5.upload it to Kaggle. A stand-alone implementation of the code described in this document can be found on th Kaggle is a well-known community website for data scientists to compete in machine learning challenges. Competitive machine learning can be a great way to hone your skills, as well as demonstrate your skills. In this article, I will provide 10 useful tips to get started with Kaggle and get good at competitive machine learning with Kaggle Team PFDet won the 2nd place in the Kaggle Open Images Challenge 2018. Google AI Open Images - Object Detection Trac 21 best open source kaggle projects. #opensource. Home; Open Source Projects; Featured Post; Tech Stack; Write For Us; We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. We aggregate information from all open source repositories. Search and find the best for your needs. Check out projects section. Tags. machine.

GitHub - RodrigoCMoraes/facialExpressionClassificationThe future of european open data portalsGoogle Releases Open Images V4 Dataset, 1Facial Expression Recognitionyangzi33 (Ziyue Yang) · GitHubBiasly | DevpostAccueil - Open Source Leader in AI and MLWhat I Learned Publishing 200+ Blog Posts on CXL

The Hardest Kaggle Challenge - YouTub

You're one of three Kaggle Quadruple Grandmasters and now we have this privilege to ask questions from someone who has aced all the four categories of Kaggle i.e Competitions, Datasets, Notebooks, and Discussions. So please tell us in detail about the challenges you faced in each aspect and also how did you overcome them? RR: Thank You! It has been one of the most exhilarating experiences of my life and I'm glad I could accomplish this feat Kaggle competitions. There are five categories of Kaggle competition: Getting Started, Playground, Featured, Research, and Recruitment. Getting Started competitions are semi-permanent, and are. Further, not all competitions are open to everyone in the world. Here's the policy of one competition, for instance: Members of the Kaggle community who are not United States Citizens or legal permanent residents at the time of entry are allowed to participate in the Competition but are not eligible to win prizes. If a team has one or more members who are not prize eligible, then the entire team is not prize eligible

Kaggle Challenge - OSICild

GitHub is where people build software. More than 56 million people use GitHub to discover, fork, and contribute to over 100 million projects Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges

First hour with a Kaggle Challenge - YouTub

20 best open source kaggle projects. #opensource. Home; Open Source Projects; Featured Post; Tech Stack; Write For Us; We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. We aggregate information from all open source repositories. Search and find the best for your needs. Check out projects section. Tags. machine. The objective of this challenge is to detect the most severe epithelial lesions of the uterine cervix. The challenge brings together thousands of microscopic slides from different medical centers across France Kaggle could have put more thought into it and minimized the damage. They could have made the challenge a master-only private competition. Such competitions have been held in the past, where participants are restricted based on Kaggle rank. Another approach would involve relying on a different competition platform for hosting the competition, where the focus would lie on soliciting.

Kaggle Released CORD-19 — an AI Challenge on the COVID-19

Here is an overview of all challenges that have been organised within the area of medical image analysis that we are aware of. Please contact us if you want to advertise your challenge or know of any study that would fit in this overview. Filter Challenges. Title or Description. Modality. CT CT/MR Dermoscopy Endoscopy Flurescein Angiography Fundus. Kaggle Earthquake Data Challenge The goal of the challenge is to predict the time remaining before laboratory earthquakes occur from real-time seismic data. The features dataset is a 629M CSV file that can be read with pandas read_csv PlantVillage is built on the premise that all knowledge that helps people grow food should be openly accessible to anyone on the planet. Explore methodology to identify assets with extreme positive or negative returns. Project 2: build our own text classifier system, and test its performance When you start a Kaggle challenge, a computer is usually needed to hold all dataset in the memory and accelerate the training with your GPU. Rather than purchasing a new computer, I'd like to do it free with 300$ credit offered by Google Cloud Platform. Step 1: Create a free account in Google Clou An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House — Read on www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge

Kaggle Challenge (LIVE) - YouTub

The challenge was to correctly identify and categorise up to 10 features and objects, such as cars, trees and buildings in a variety of environments. The project has the potential to identify. Kaggle competition solutions. Your Home for Data Science. Kaggle helps you learn, work and play. Kaggle is one of the most popular data science competitions hub. Which offers a wide range of real-world data science problems to challenge each and every data scientist in the world The contest is now open on Kaggle opened participants to enter the competition on Kaggle, with an entry deadline of May 28th and final submissions due on June 4th. So far 14 teams have registered, which is a much lower number than the 127 for the Google Landmark Challenge which is running simultaneously and also within the remit of CVPR 2018

Top Competitive Data Science Platforms other than Kaggle

Browse the challenges currently available on Topcoder. Search by type of challenge, then find those of interest to register for and compete in today Building on challenges with processing image data, another Kaggle competition David participated in was the State Farm Distracted Driver Detection challenge. The problem was to identify distracted drivers by reviewing images to determine whether the driver was doing things like playing with the radio, using the phone or applying makeup The test set has the same 100k images as the 2018 Challenge and will be launched again on June 3rd, 2019 by Kaggle. The evaluation servers will open on June 3rd for the object detection and visual relationship tracks, and on July 1st for the instance segmentation track. The deadline for submission of results is October 1st, 2019 The LUNA16 challenge is therefore a completely open challenge. We have tracks for complete systems for nodule detection, and for systems that use a list of locations of possible nodules. We provide this list to also allow teams to participate with an algorithm that only determines the likelihood for a given location in a CT scan to contain a pulmonary nodule The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without the users or the films being identified except by numbers assigned for the contest. The competition was held by Netflix, an online DVD-rental and video streaming service, and was open to anyone who is neither connected with Netflix nor a resident of certain blocked. Jul 26, 2017: We are passing the baton to Kaggle. From now on, all three challenges(LOC-CLS, DET, VID) will be hosted on Kaggle! Jul 17, 2017: Results announced. Jun 25, 2017: Submission server for VID is open, new additional train/val/test images for VID is available now, deadline for VID is extended to July 7, 2017 5pm PDT. Jun 18, 2017: Submission server for CLS-LOC and DET is open. Jun 15.

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