I'm pursuing my final year of Bachelor of Technology and my core branch is Information and Communication Technology. You May Also Enjoy. Learn currently hosts tutorials about 4 topics - introductory machine learning, R programming, data visualisation and deep learning. Awesome Deep Learning resources; Tags: Kaggle. ~0.96 on Kaggle IMDB using stupid learning instead of "deep learning" - model.py ~0.96 on Kaggle IMDB using stupid learning instead of "deep learning" - model.py . PDPU Open Source Developer. I also have the Jupyter Notebook version of some of my Kaggle kernels here. For this week’s ML practitioner’s series, we got in touch with Kaggle Grandmaster Martin Henze.Martin is an astrophysicist by training who ventured into machine learning fascinated by data. Deep Learning for NLP. Anybody wants to do a Kaggle competition as a team? Self-Driving Deep Learning. View Nov 2016. View Sep 2017. Course info. As the lecture describes, deep learning discovers ways to represent the world so that we can reason about it. I started using Kaggle seriously a couple of months ago when I joined the SIIM-ISIC Melanoma Classification Competition. Installing the library. Connect with me: LinkedIn; Github; Kaggle (Contributor) Medium; Email; Skills. Advanced Topics in Deep Learning Instructor: Yuan Yao Due: 23:59 Sunday 15 Dec, 2018 1 Requirement This project as a warm-up aims to explore feature extractions using existing networks, such as pre-trained deep neural networks and scattering nets, in image classi cations with traditional machine learning methods. Anybody wants to do a Kaggle competition as a team? Close. I used data from iWildCam 2020 Kaggle competition to practice machine learning vision after completing fast.ai’s deep learning course. Projects: Kaggle SIIM-ISIC-Melanoma-Classification Competition 130/3314 (Silver Medal) [Link for the complete project repository] Identify melanoma in images of skin lesions. Kaggle GitHub Recent Posts. Share on Twitter Facebook Google+ LinkedIn Previous Next. Machine Learning. Google Colab — Google’s free cloud service for AI developers. With Colab, you can develop deep learning applications on … Deep Learning for Practical Image Recognition: Case Study on Kaggle Competitions Xulei Yang* Institute for Infocomm Research yang_xulei@i2r.a-star.edu.sg Zeng Zeng Institute for Infocomm Research zengz@i2r.a-star.edu.sg Sin G. Teo Institute for Infocomm Research teosg@i2r.a-star.edu.sg Li Wang Institute for Infocomm Research wang_li@i2r.a-star.edu.sg Vijay Chandrasekhar Institute for … I think it would be a great learning experience. Although this project is far from complete but it is remarkable to see the success of deep learning in such varied real world problems. (and why you should) 3 minute read Kaggle is the biggest Data Science community with over 2 million … I have demonstrated how to classify positive and negative pneumonia data from a collection of X-ray images. Learn how software engineering best practices, such as layered API design and decoupling, have allowed … A lot of Tensorflow popularity among practitioners … My Kaggle profile My Portfolio-Website (vatsalparsaniya.github.io) Other Projects. Posted by 9 hours ago. GitHub is where the world builds software. Deep learning has vast ranging applications and its application in the healthcare industry always fascinates me. View Mar 2017. Setting up Kaggle API on Mac/Linux. Working with the organization's … 6 min read. Welcome … As a keen learner and a Kaggle noob, I decided to work on the Malaria Cells dataset to get some hands-on experience and learn how to work with Convolutional Neural Networks, Keras and images on the Kaggle platform. Created Dec 11, 2014. Explore and run machine learning code with Kaggle Notebooks | Using data from Huge Stock Market Dataset Blog About. Overview Foreseeing bugs, features, and questions on GitHub can be fun, especially when one is provided with a colossal dataset containing the GitHub issues. Selected Projects. text data, transfer learning. Star 6 Fork 0; Star Code Revisions 1 Stars 6. You can set a dataset created from a URL or GitHub … Severstal Steel Defect Detection Challenge on Kaggle Top 2 % (31/2431 ... which provides dozens of pretrained heads to Unet and other unet-like architectures. In recent years we witnessed a huge development in machine learning, especially in deep learning which drives a new technological revolution. Currently working as a Data Scientist with TimeSeries (IoT) domain, design machine learning experiments and developing efficient sequence … deep learning library: 1015 W8: project plan checkup: 1020 W9: HW1 + HW2 discussions: 1022 W9: Quiz 1-5 discussions: 1027 W10 : HW3 discussions: 1029 W10: Slides W9-10 discussions: 1103 W11: Invited speaker RLGym: 1105 W11: Invited speaker TextAttack: 1110 W12: W11-12 Slides discussions: 1112 W12: project midreport checkup: 1117 W13: HW3, HW4 discussions: 1119 W13: Quiz 6-11 … Student. I am currently pursuing Machine Learning and Deep Learning. Selected Competitions. 1. 1. Image-Based Localization Challenge. A lot of Tensorflow popularity among practitioners is due to Keras, which API... How to start with Kaggle? Newmu / model.py. More Event Management Head. I'd stumbled across machine learning for the first time in the form of neural networks (NN) more than 3 years back. Prior to joining WashU, I did my Bachelors degree in Electrical Engineering from Jadavpur University in India, where I worked on … Cityscapes Semantic Segmentation. His notebooks on Kaggle are a must read where he brings his decade long expertise in handling vast data into play. If you asked me 6 months ago how to play a Kaggle competition, you probably get the above answer. Write a paper that describes your solution to the machine learning competition . I have been contributing to projects from different open source organisations on Github. "Hamel Husain (Staff Machine Learning Engineer at GitHub) will moderate the talk. If you are like me and want to use Kaggle API instead of manual clicks here and there on the Kaggle website to get your task done, this post is for you! This is a new series for my channel where I will be going over many different kaggle kernels that I have created for computer vision experiments/projects. Deep Learning Computer Vision. By using Kaggle, you agree to our use of cookies. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Hello! The model was made from scratch, which separates it from other methods that rely heavily on transfer learning approach. The code in the GitHub link is also written on Google Colab. Very recently, I notices some top Kagglers apply (deep) neural network to win data mining competitions. Hypothesis Building, … The rest is clever methods that help use deal effectively with visual information, language, sound (#1-6) and even act in a world based on this information and occasional rewards (#7). For the full code go to Github. Deep Learning Frameworks Speed Benchmark - Update, Vol I 2 minute read Two Deep Learning frameworks gather biggest attention - Tensorflow and Pytorch. I am more interested in tabular data. Predicitive & Descriptive, Supervised (Regression & Classification), Actively pursuing Unsupervised ML ; Statistics & Mathematics. But still, this model can return good accuracies and can further can be enhanced. TL;DR. Contact: minesh.1291@gmail.com, LinkedIn, Kaggle, Github. Self-Driving Computer Vision. View On GitHub; This project is maintained by patbaa. and 2 more. I work in the Adaptive Integrated Microsystems Lab, advised by Professor Shantanu Chakrabartty. Note: This post is most useful for folks using a Mac or a Linux environment. The main focus of the blog is Self-Driving Car Technology and Deep Learning. Blog post: Forensic Deep Learning: Kaggle Camera Model Identification Challenge; IX: Days. I managed to build a solution that achieved 78% accuracy on the test set in classifying animals on the camera trap photo, which places the solution in the top 10% of this competition (10/126). There are several pros and cons of using Deep Learning to tackle such kinds of situations: Pros: More time saving; less expensive; easy to operate; Cons: Practically we need ~100% accuracy as we can’t wrongly identify the patients as it might lead to further spread of disease which is highly discouraged. These models improve searches, apps, social media and open new doors in medicine, automation, self-driving cars, drones and almost all fields of science. Data Scientist, machine learning engineer, with extensive experience with developing algorithms, statistical models and deep learning architectures using Python in a Big Data environment. You can create public and private datasets on Kaggle from your local machine, URLs, GitHub repositories, and Kaggle Notebook outputs. GitHub; Kaggle; Hello! Embed. Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic: Machine Learning from Disaster Updated: November 28, 2018. Deep Learning: Towards Deeper Understanding 28 Nov, 2018 Final Project. Vehicle and Lane Lines Detection . The initial reason, I think, was that I wanted a serious way to test my Machine Learning (ML) and Deep Learning (DL) skills. One of the many things I like about Kaggle is t he … All gists Back to GitHub Sign in Sign up Sign in Sign up {{ message }} Instantly share code, notes, and snippets. November 2, join Jeremy Howard (Researcher & Co-Founder at fast.ai; past President & Chief Scientist at Kaggle) for the free ACM TechTalk, "It's Time Deep Learning Learned from Software Engineering. Data Science | AI | Deep Learning. Skip to content. Passionate about building Machine-Learning, Deep-Learning, Computer-Vision projects. And it is prepared using content (theory and code) from following sources: Deep Learning with Python, Book by François Chollet; Neural Network Methods in Natural Language Processing, Book by Yoav Goldberg Description . I am Oindrila, a PhD Candidate in the Electrical and Systems Engineering Department at Washington University in St.Louis, Missouri. ANN built to predict passenger survival on the Titanic - dkhaage/Deep-Learning-Kaggle-Competition GitHub Bugs Prediction Challenge (Machine Hack) GitHub Bugs Prediction Challenge (Machine Hack) ... deep learning x 10596. technique > deep learning. Let’s get started! Hello there! Why Kaggle? Link to dataset. Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. Leave a Comment. It is not the reason why I write this article. Includes Machine Learning and Deep Learning, Data Analysis projects on datasets from Kaggle - pranaymodukuru/Kaggle-projects 5 7 75. Deep Learning Frameworks Speed Benchmark - Update, Vol I 2 minute read Two Deep Learning frameworks gather biggest attention - Tensorflow and Pytorch. 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