Satya Borgohain's Projects
This repo is dedicated to the EDA for Coral bleaching in the Great Barrier Reef. It primarily focused on 8 sites with 5 different types of Corals. This project was a template for exploring different types of visualizations & EDA performed on the same dataset, using Tableau, R & d3.js
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)
List of AI Residency Programs
:memo: An awesome Data Science repository to learn and apply for real world problems.
A curated list of awesome Deep Learning tutorials, projects and communities.
Notebooks about Bayesian methods for machine learning
Bayesian Data Analysis demos for Python
Code and experiments for the preprint: "Bayesian Neural Network Versus Ex-Post Calibration For Capturing Prediction Uncertainty".
Essential Cheat Sheets for deep learning and machine learning researchers
Company names matching: match company names to legal names and stock symbols
A technical report on convolution arithmetic in the context of deep learning
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A R+Rshiny implementation for analysis of Coral bleaching in the Great barrier reef.
Reusable, general purpose code.
Kaggle competition on birdcall classification.
A Code-First Introduction to NLP course
The 3rd edition of course.fast.ai
Public facing notes page
A custom image classifier based on the fast.ai library. The code can be used as a template to train a CNN with resnet34 architecture (other variants as well) on any custom dataset. Credits to fastai.
Dive into Deep Learning: an interactive deep learning book with code, math, and discussions, based on the NumPy interface.
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.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
📡 Notes + Code from studying Digital Signal Processing
DyNet: The Dynamic Neural Network Toolkit
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Draft of the fastai book
Generative Art.
Experiments with generative art and cellular automata.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent