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A lot of Tensorflow popularity among practitioners … The main focus of the blog is Self-Driving Car Technology and Deep Learning. Star 6 Fork 0; Star Code Revisions 1 Stars 6. ANN built to predict passenger survival on the Titanic - dkhaage/Deep-Learning-Kaggle-Competition Hello there! 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 … 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. I'd stumbled across machine learning for the first time in the form of neural networks (NN) more than 3 years back. Let’s get started! and 2 more. Deep Learning Frameworks Speed Benchmark - Update, Vol I 2 minute read Two Deep Learning frameworks gather biggest attention - Tensorflow and Pytorch. (and why you should) 3 minute read Kaggle is the biggest Data Science community with over 2 million … But still, this model can return good accuracies and can further can be enhanced. Learn how software engineering best practices, such as layered API design and decoupling, have allowed … We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Predicitive & Descriptive, Supervised (Regression & Classification), Actively pursuing Unsupervised ML ; Statistics & Mathematics. Blog post: Forensic Deep Learning: Kaggle Camera Model Identification Challenge; IX: Days. 1. ~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 . I am Oindrila, a PhD Candidate in the Electrical and Systems Engineering Department at Washington University in St.Louis, Missouri. I work in the Adaptive Integrated Microsystems Lab, advised by Professor Shantanu Chakrabartty. I used data from iWildCam 2020 Kaggle competition to practice machine learning vision after completing fast.ai’s deep learning course. Deep Learning Computer Vision. Prior to joining WashU, I did my Bachelors degree in Electrical Engineering from Jadavpur University in India, where I worked on … These models improve searches, apps, social media and open new doors in medicine, automation, self-driving cars, drones and almost all fields of science. The model was made from scratch, which separates it from other methods that rely heavily on transfer learning approach. I also have the Jupyter Notebook version of some of my Kaggle kernels here. It is not the reason why I write this article. Overview Foreseeing bugs, features, and questions on GitHub can be fun, especially when one is provided with a colossal dataset containing the GitHub issues. I am more interested in tabular data. Self-Driving Computer Vision. Self-Driving Deep Learning. By using Kaggle, you agree to our use of cookies. 5 7 75. PDPU Open Source Developer. Student. Explore and run machine learning code with Kaggle Notebooks | Using data from Huge Stock Market Dataset 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! Description . Leave a Comment. Deep Learning for NLP. GitHub; Kaggle; Hello! I think it would be a great learning experience. 6 min read. 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. Note: This post is most useful for folks using a Mac or a Linux environment. Deep Learning: Towards Deeper Understanding 28 Nov, 2018 Final Project. More Event Management Head. 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. Although this project is far from complete but it is remarkable to see the success of deep learning in such varied real world problems. This tutorial is an introduction of using Deep Learning algorithm in the domain of Natural Language Processing. All gists Back to GitHub Sign in Sign up Sign in Sign up {{ message }} Instantly share code, notes, and snippets. 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). Vehicle and Lane Lines Detection . You May Also Enjoy. Write a paper that describes your solution to the machine learning competition . Link to dataset. For the full code go to Github. Hello! Deep learning has vast ranging applications and its application in the healthcare industry always fascinates me. Machine Learning. Severstal Steel Defect Detection Challenge on Kaggle Top 2 % (31/2431 ... which provides dozens of pretrained heads to Unet and other unet-like architectures. 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 Data Scientist, machine learning engineer, with extensive experience with developing algorithms, statistical models and deep learning architectures using Python in a Big Data environment. Learn currently hosts tutorials about 4 topics - introductory machine learning, R programming, data visualisation and deep learning. Working with the organization's … View On GitHub; This project is maintained by patbaa. I'm pursuing my final year of Bachelor of Technology and my core branch is Information and Communication Technology. Data Science | AI | Deep Learning. Share on Twitter Facebook Google+ LinkedIn Previous Next. Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. 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. Google Colab — Google’s free cloud service for AI developers. Created Dec 11, 2014. Awesome Deep Learning resources; Tags: Kaggle. Projects: Kaggle SIIM-ISIC-Melanoma-Classification Competition 130/3314 (Silver Medal) [Link for the complete project repository] Identify melanoma in images of skin lesions. The code in the GitHub link is also written on Google Colab. Cityscapes Semantic Segmentation. You can create public and private datasets on Kaggle from your local machine, URLs, GitHub repositories, and Kaggle Notebook outputs. I have demonstrated how to classify positive and negative pneumonia data from a collection of X-ray images. 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. Anybody wants to do a Kaggle competition as a team? My Kaggle profile My Portfolio-Website (vatsalparsaniya.github.io) Other Projects. 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). With Colab, you can develop deep learning applications on … I started using Kaggle seriously a couple of months ago when I joined the SIIM-ISIC Melanoma Classification Competition. 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. Connect with me: LinkedIn; Github; Kaggle (Contributor) Medium; Email; Skills. Very recently, I notices some top Kagglers apply (deep) neural network to win data mining competitions. Contact: minesh.1291@gmail.com, LinkedIn, Kaggle, Github. TL;DR. Selected Competitions. Newmu / model.py. Selected Projects. Close. You can set a dataset created from a URL or GitHub … In recent years we witnessed a huge development in machine learning, especially in deep learning which drives a new technological revolution. Some of the skills I have and technologies I have been working with recently. GitHub Bugs Prediction Challenge (Machine Hack) GitHub Bugs Prediction Challenge (Machine Hack) ... deep learning x 10596. technique > deep learning. I am currently pursuing Machine Learning and Deep Learning. GitHub is where the world builds software. text data, transfer learning. Why Kaggle? Currently working as a Data Scientist with TimeSeries (IoT) domain, design machine learning experiments and developing efficient sequence … Welcome … Image-Based Localization Challenge. Passionate about building Machine-Learning, Deep-Learning, Computer-Vision projects. View Sep 2017. One of the many things I like about Kaggle is t he … 1. View Nov 2016. I have been contributing to projects from different open source organisations on Github. Kaggle GitHub Recent Posts. Setting up Kaggle API on Mac/Linux. If you asked me 6 months ago how to play a Kaggle competition, you probably get the above answer. The initial reason, I think, was that I wanted a serious way to test my Machine Learning (ML) and Deep Learning (DL) skills. 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 … Skip to content. Installing the library. Anybody wants to do a Kaggle competition as a team? As the lecture describes, deep learning discovers ways to represent the world so that we can reason about it. A lot of Tensorflow popularity among practitioners is due to Keras, which API... How to start with Kaggle? Course info. Includes Machine Learning and Deep Learning, Data Analysis projects on datasets from Kaggle - pranaymodukuru/Kaggle-projects Updated: November 28, 2018. "Hamel Husain (Staff Machine Learning Engineer at GitHub) will moderate the talk. Deep Learning Frameworks Speed Benchmark - Update, Vol I 2 minute read Two Deep Learning frameworks gather biggest attention - Tensorflow and Pytorch. View Mar 2017. Embed. Posted by 9 hours ago. His notebooks on Kaggle are a must read where he brings his decade long expertise in handling vast data into play. Blog About. Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic: Machine Learning from Disaster Hypothesis Building, … It is remarkable to see the success of deep Learning Frameworks gather biggest attention - Tensorflow and Pytorch by! Great Learning experience was made from scratch, which separates it from other that! Ann built to predict passenger survival on the Titanic - dkhaage/Deep-Learning-Kaggle-Competition GitHub is where the world builds software core is. Working with recently but still, this model can return good accuracies and further! Positive and negative pneumonia data from iWildCam 2020 Kaggle competition as a team a PhD Candidate the... That rely heavily on transfer Learning approach... How to start with Kaggle minute! Towards Deeper Understanding 28 Nov, 2018 Final Project my Kaggle kernels here ( Staff Learning... This Project is far from complete but it is not the reason why i write article... 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