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
Denoising Diffusion Probabilistic Models

Denoising Diffusion Probabilistic Models This repo contains code for DDPM training. Based on Denoising Diffusion Probabilistic Models, Improved Denois

Alexander Markov 7 Dec 15, 2022
Parametric Contrastive Learning (ICCV2021)

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

DV Lab 156 Dec 21, 2022
FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows

FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows.

Meta Incubator 272 Jan 02, 2023
AI Toolkit for Healthcare Imaging

Medical Open Network for AI MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem. Its am

Project MONAI 3.7k Jan 07, 2023
Offline Reinforcement Learning with Implicit Q-Learning

Offline Reinforcement Learning with Implicit Q-Learning This repository contains the official implementation of Offline Reinforcement Learning with Im

Ilya Kostrikov 126 Jan 06, 2023
MILK: Machine Learning Toolkit

MILK: MACHINE LEARNING TOOLKIT Machine Learning in Python Milk is a machine learning toolkit in Python. Its focus is on supervised classification with

Luis Pedro Coelho 610 Dec 14, 2022
This repository contains a PyTorch implementation of the paper Learning to Assimilate in Chaotic Dynamical Systems.

Amortized Assimilation This repository contains a PyTorch implementation of the paper Learning to Assimilate in Chaotic Dynamical Systems. Abstract: T

4 Aug 16, 2022
Code for Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021)

Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021) Single-cause Perturbation (SCP) is a framework to estimate the m

Zhaozhi Qian 9 Sep 28, 2022
pytorch implementation of dftd2 & dftd3

torch-dftd pytorch implementation of dftd2 [1] & dftd3 [2, 3] Install # Install from pypi pip install torch-dftd # Install from source (for developer

33 Nov 28, 2022
[TIP 2020] Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion

Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion Code for Multi-Temporal Scene Classification and Scene Ch

Lixiang Ru 33 Dec 12, 2022
Official code for Score-Based Generative Modeling through Stochastic Differential Equations

Score-Based Generative Modeling through Stochastic Differential Equations This repo contains the official implementation for the paper Score-Based Gen

Yang Song 818 Jan 06, 2023
Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option

Amazon Web Services - Labs 236 Jan 01, 2023
Implementation for our ICCV2021 paper: Internal Video Inpainting by Implicit Long-range Propagation

Implicit Internal Video Inpainting Implementation for our ICCV2021 paper: Internal Video Inpainting by Implicit Long-range Propagation paper | project

202 Dec 30, 2022
This is the dataset for testing the robustness of various VO/VIO methods

KAIST VIO dataset This is the dataset for testing the robustness of various VO/VIO methods You can download the whole dataset on KAIST VIO dataset Ind

1 Sep 01, 2022
High-Resolution 3D Human Digitization from A Single Image.

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization (CVPR 2020) News: [2020/06/15] Demo with Google Colab (i

Meta Research 8.4k Dec 29, 2022
some academic posters as references. May we have in-person poster session soon!

some academic posters as references. May we have in-person poster session soon!

Bolei Zhou 472 Jan 06, 2023
'Aligned mixture of latent dynamical systems' (amLDS) for stimulus decoding probabilistic manifold alignment across animals. P. Herrero-Vidal et al. NeurIPS 2021 code.

Across-animal odor decoding by probabilistic manifold alignment (NeurIPS 2021) This repository is the official implementation of aligned mixture of la

Pedro Herrero-Vidal 3 Jul 12, 2022
TensorFlow (Python API) implementation of Neural Style

neural-style-tf This is a TensorFlow implementation of several techniques described in the papers: Image Style Transfer Using Convolutional Neural Net

Cameron 3.1k Jan 02, 2023
GAN-based 3D human pose estimation model for 3DV'17 paper

Tensorflow implementation for 3DV 2017 conference paper "Adversarially Parameterized Optimization for 3D Human Pose Estimation". @inproceedings{jack20

Dominic Jack 15 Feb 27, 2021
Implementation of Bagging and AdaBoost Algorithm

Bagging-and-AdaBoost Implementation of Bagging and AdaBoost Algorithm Dataset Red Wine Quality Data Sets For simplicity, we will have 2 classes of win

Zechen Ma 1 Nov 01, 2021