Self-Learning - Books Papers, Courses & more I have to learn soon

Overview

Self-Learning

This repository is intended to be used for personal use, all rights reserved to respective owners, please cite original authors and ask for permissions as specified in any document present here-in

Study Material

Basic

  • Linear Algebra Gilbert Strang
  • Probability & Statistics basics
  • Hands On Machine learning Book
  • Piyush Rai Slides, IIT-K
  • [ ]

Advanced

  • Elements of Statistical Learning Theory
  • Pattern Recognition & Machine Learning .Bishop
  • Deep learning .Goodfellow
  • Reinforcement Learning
  • Time Series
  • [ ]

DeepLearning.Ai

  • Deep Learning Specialization
  • Tensorflow in Practice
  • Tensorflow: Data & Deployment
  • AI for Everyone

YouTube Courses

  • 3Blue1Brown (LA, Calculus, DiffEq, Neural Networks)
  • Advanced Deep & Reinforcement Learning
  • Reinforcement Learning - David Silver

MIT-OCW

  • Linear Algebra
  • Introduction to Probability
  • Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
  • Introduction to Algorithms
  • Design and Analysis of Algorithms

NPTEL

  • Numerical Optimization
  • Pattern Recognition and Neural Networks

Stanford

  • Natural Language Understanding
  • NLP with Deep Learning
  • Deep Learning
  • Reinforcement Learning

Projects

  • Image Classification
  • SISR, CAR, Denoising
  • Sentiment Analysis/Classification
  • Adversarial Machine Learning
  • Style Transfer/Generation
  • Time Series Forecasting
  • Cardinality Estimation
  • [ ]
  • Question Answering
  • Speech Synthesis
  • Text to SQL
  • Audio Source Separation
  • [ ]
  • [ ]
conda update conda
conda create -n py38 python=3.8
conda activate py38
conda install numpy scipy sympy matplotlib seaborn holoviews panel bokeh pandas scikit-learn scikit-image pillow ipython jupyter numba joblib dask dask-ml h2o django flask gevent requests lightgbm catboost nltk imbalanced-learn
pip install --upgrade opencv-python streamlit jupyter_http_over_ws xgboost
pip install --upgrade tensorflow keras-tuner
conda update --all

import tensorflow as tf
tf.config.list_physical_devices('GPU')

jupyter serverextension enable --py jupyter_http_over_ws
jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --port=6006 --NotebookApp.port_retries=0

conda create -n py38 python=3.8 --no-default-packages
conda remove -n py38 --all

conda install -c anaconda-nb-extensions nb_conda
conda install -c anaconda psycopg2

# Teamviewer Not Launching in Ubuntu18.04
systemctl restart teamviewerd

python 

SciPy Stack (Numpy, Matplotlib, Pandas, SymPy & Scipy Included)

https://scipy.org

SEABORN (Powerful pretty plotting library)

https://seaborn.pydata.org

Scikit-Learn (Standard ML and many algorithms implemented)

https://scikit-learn.org/stable/

High-level Neural Network API (Yet customizable)

https://keras.io

Visualising Neural Network Training, Computation graph and a lot

https://www.tensorflow.org/tensorboard

Backend for Keras, Powerful tool for ML/DL & Simulation research

https://www.tensorflow.org

Distributed load balanced data handling (over-system & clusters)

https://dask.org

ML implementation of Most Scikit-learn Algorithms, highly scalable

https://ml.dask.org

Great examples on how to use DASK

https://examples.dask.org

Machine learning, Data processing & more on Nvidia GPU

https://rapids.ai

Building High level data apps with Ease

https://www.streamlit.io

TF projector for visualization with Dimensionality reduction

https://projector.tensorflow.org

Creating VMs (Infra+Platform) over GCP

https://console.cloud.google.com/getting-started

Codelabs provide a Step-wise, learning tutorials, hands-on coding experience. To build a small application OR adding features into existing application

https://codelabs.developers.google.com

Connecting Google colab notebooks to local runtime

https://research.google.com/colaboratory/local-runtimes.html

Connecting Google Colab to Local Runtime

pip install jupyter_http_over_ws

jupyter serverextension enable --py jupyter_http_over_ws

jupyter notebook
--NotebookApp.allow_origin='https://colab.research.google.com'
--port=6006
--NotebookApp.port_retries=0

https://github.com/quantopian/zipline https://github.com/EliteQuant/EliteQuant https://github.com/ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network

Windows/Linux Utility Software

  • 7-zip
  • Adobe Reader DC
  • Anaconda3
  • AnyDesk
  • AOMEI Partition Wizard
  • CISCO AnyConnect
  • Dev-C++
  • Free Download Manager
  • Git
  • Google Chrome
  • Java SDK
  • MS Office/One-Drive
  • VS Code
  • Mozilla Firefox
  • PostgreSQL
  • PowerISO
  • Putty
  • Samsung Magician
  • Spotify
  • Sublime Text 3
  • TeamViewer
  • Universal ADB driver for Vysor
  • VLC Media Player
  • WinRAR
  • WinSCP

Hobby-Projects

Owner
Achint Chaudhary
Computer Science Masters at Indian Institute of Science, Bangalore
Achint Chaudhary
docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

Mindee 1.5k Jan 01, 2023
Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu

150 Dec 26, 2022
Repository for publicly available deep learning models developed in Rosetta community

trRosetta2 This package contains deep learning models and related scripts used by Baker group in CASP14. Installation Linux/Mac clone the package git

81 Dec 29, 2022
Bringing Computer Vision and Flutter together , to build an awesome app !!

Bringing Computer Vision and Flutter together , to build an awesome app !! Explore the Directories Flutter · Machine Learning Table of Contents About

Padmanabha Banerjee 14 Apr 07, 2022
Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment

Preference-Planning-Deep-IRL Introduction Check my portfolio post Dependencies Gym stable-baselines3 PyTorch Usage Take Demonstration python3 record.

Tianyu Li 9 Oct 26, 2022
Self-Supervised CNN-GCN Autoencoder

GCNDepth Self-Supervised CNN-GCN Autoencoder GCNDepth: Self-supervised monocular depth estimation based on graph convolutional network To be published

53 Dec 14, 2022
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms

FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,

Rishikesh (ऋषिकेश) 218 Jan 05, 2023
AdamW optimizer and cosine learning rate annealing with restarts

AdamW optimizer and cosine learning rate annealing with restarts This repository contains an implementation of AdamW optimization algorithm and cosine

Maksym Pyrozhok 133 Dec 20, 2022
Adversarially Learned Inference

Adversarially Learned Inference Code for the Adversarially Learned Inference paper. Compiling the paper locally From the repo's root directory, $ cd p

Mohamed Ishmael Belghazi 308 Sep 24, 2022
Fully Convolutional Refined Auto Encoding Generative Adversarial Networks for 3D Multi Object Scenes

Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes This repository contains the source code for Full

Yu Nishimura 106 Nov 21, 2022
Shuffle Attention for MobileNetV3

SA-MobileNetV3 Shuffle Attention for MobileNetV3 Train Run the following command for train model on your own dataset: python train.py --dataset mnist

Sajjad Aemmi 36 Dec 28, 2022
Official PyTorch implementation of UACANet: Uncertainty Aware Context Attention for Polyp Segmentation

UACANet: Uncertainty Aware Context Attention for Polyp Segmentation Official pytorch implementation of UACANet: Uncertainty Aware Context Attention fo

Taehun Kim 85 Dec 14, 2022
Exploiting Robust Unsupervised Video Person Re-identification

Exploiting Robust Unsupervised Video Person Re-identification Implementation of the proposed uPMnet. For the preprint, please refer to [Arxiv]. Gettin

1 Apr 09, 2022
the official code for ICRA 2021 Paper: "Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation"

G2S This is the official code for ICRA 2021 Paper: Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation by Hemang

NeurAI 4 Jul 27, 2022
Official git for "CTAB-GAN: Effective Table Data Synthesizing"

CTAB-GAN This is the official git paper CTAB-GAN: Effective Table Data Synthesizing. The paper is published on Asian Conference on Machine Learning (A

30 Dec 26, 2022
A new test set for ImageNet

ImageNetV2 The ImageNetV2 dataset contains new test data for the ImageNet benchmark. This repository provides associated code for assembling and worki

186 Dec 18, 2022
MLSpace: Hassle-free machine learning & deep learning development

MLSpace: Hassle-free machine learning & deep learning development

abhishek thakur 293 Jan 03, 2023
RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation

RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation Anonymous submission Abstract 3D obj

30 Sep 16, 2022
[NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)

Are Transformers More Robust Than CNNs? Pytorch implementation for NeurIPS 2021 Paper: Are Transformers More Robust Than CNNs? Our implementation is b

Yutong Bai 145 Dec 01, 2022
Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation

CaloGAN Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. This repository c

Deep Learning for HEP 101 Nov 13, 2022