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
Code for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in Deep Latent Space"

SRHEN This is a better and simpler implementation for "SRHEN: Stepwise-Refining Homography Estimation Network via Parsing Geometric Correspondences in

1 Oct 28, 2022
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".

Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw

Zhuang AI Group 30 Dec 19, 2022
Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC. Para los Laboratorios de la materia, vamos a utilizar el len

Luis Biedma 18 Dec 12, 2022
Official PyTorch implementation of Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations

Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, Yu

UT-Austin Robot Perception and Learning Lab 63 Jan 03, 2023
Improving Transferability of Representations via Augmentation-Aware Self-Supervision

Improving Transferability of Representations via Augmentation-Aware Self-Supervision Accepted to NeurIPS 2021 TL;DR: Learning augmentation-aware infor

hankook 38 Sep 16, 2022
Yolov5-lite - Minimal PyTorch implementation of YOLOv5

Yolov5-Lite: Minimal YOLOv5 + Deep Sort Overview This repo is a shortened versio

Kadir Nar 57 Nov 28, 2022
Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

Microsoft 344 Dec 29, 2022
TimeSHAP explains Recurrent Neural Network predictions.

TimeSHAP TimeSHAP is a model-agnostic, recurrent explainer that builds upon KernelSHAP and extends it to the sequential domain. TimeSHAP computes even

Feedzai 90 Dec 18, 2022
Generate images from texts. In Russian

ruDALL-E Generate images from texts pip install rudalle==1.1.0rc0 🤗 HF Models: ruDALL-E Malevich (XL) ruDALL-E Emojich (XL) (readme here) ruDALL-E S

AI Forever 1.6k Dec 31, 2022
[NeurIPS'21] Projected GANs Converge Faster

[Project] [PDF] [Supplementary] [Talk] This repository contains the code for our NeurIPS 2021 paper "Projected GANs Converge Faster" by Axel Sauer, Ka

798 Jan 04, 2023
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence

Neural Circuit Policies Enabling Auditable Autonomy Online access via SharedIt Neural Circuit Policies (NCPs) are designed sparse recurrent neural net

8 Jan 07, 2023
An open-source outlier detection package by Getcontact Data Team

pyfbad The pyfbad library supports anomaly detection projects. An end-to-end anomaly detection application can be written using the source codes of th

Teknasyon Tech 41 Dec 27, 2022
Tensor-Based Quantum Machine Learning

TensorLy_Quantum TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch. Website: h

TensorLy 85 Dec 03, 2022
Estimation of human density in a closed space using deep learning.

Siemens HOLLZOF challenge - Human Density Estimation Add project description here. Installing Dependencies: Install Python3 either system-wide, user-w

3 Aug 08, 2021
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble This is the code for reproducing the results of the paper Uncertainty-Bas

43 Nov 23, 2022
Reimplementation of Dynamic Multi-scale filters for Semantic Segmentation.

Paddle implementation of Dynamic Multi-scale filters for Semantic Segmentation.

Hongqiang.Wang 2 Nov 01, 2021
The aim of the game, as in the original one, is to find a specific image from a group of different images of a person's face

GUESS WHO Main Links: [Github] [App] Related Links: [CLIP] [Celeba] The aim of the game, as in the original one, is to find a specific image from a gr

Arnau - DIMAI 3 Jan 04, 2022
Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis

Pyramid Transformer Net (PTNet) Project | Paper Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis. PTNet: A Hi

Xuzhe Johnny Zhang 6 Jun 08, 2022
PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning

PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning Warning: This is a rapidly evolving research prototype.

MIT Probabilistic Computing Project 190 Dec 27, 2022
AugLiChem - The augmentation library for chemical systems.

AugLiChem Welcome to AugLiChem! The augmentation library for chemical systems. This package supports augmentation for both crystaline and molecular sy

BaratiLab 17 Jan 08, 2023