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
Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2021)

Applied Machine Learning (Cornell CS5785, Fall 2021) This repo contains executable course notes and slides for the Applied ML course at Cornell and Co

Volodymyr Kuleshov 103 Dec 31, 2022
Official implementation for “Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior”

HEP Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior Implementation Python3 PyTorch=1.0 NVIDIA GPU+CUDA Training process The

FengZhang 34 Dec 04, 2022
A flexible submap-based framework towards spatio-temporally consistent volumetric mapping and scene understanding.

Panoptic Mapping This package contains panoptic_mapping, a general framework for semantic volumetric mapping. We provide, among other, a submap-based

ETHZ ASL 194 Dec 20, 2022
PyTorch implementation of paper A Fast Knowledge Distillation Framework for Visual Recognition.

FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f

Zhiqiang Shen 129 Dec 24, 2022
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)

GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G

MRSAIL (Mini Robotics, Software & AI Lab) 6 Nov 26, 2022
Source code for the paper "Periodic Traveling Waves in an Integro-Difference Equation With Non-Monotonic Growth and Strong Allee Effect"

Source code for the paper "Periodic Traveling Waves in an Integro-Difference Equation With Non-Monotonic Growth and Strong Allee Effect" by Michael Ne

M Nestor 1 Apr 19, 2022
Beancount-mercury - Beancount importer for Mercury Startup Checking

beancount-mercury beancount-mercury provides an Importer for converting CSV expo

Michael Lynch 4 Oct 31, 2022
Provably Rare Gem Miner.

Provably Rare Gem Miner just another random project by yoyoismee.eth useful link main site market contract useful thing you should know read contract

34 Nov 22, 2022
PyTorch implementation of the ideas presented in the paper Interaction Grounded Learning (IGL)

Interaction Grounded Learning This repository contains a simple PyTorch implementation of the ideas presented in the paper Interaction Grounded Learni

Arthur Juliani 4 Aug 31, 2022
这是一个unet-pytorch的源码,可以训练自己的模型

Unet:U-Net: Convolutional Networks for Biomedical Image Segmentation目标检测模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Downl

Bubbliiiing 567 Jan 05, 2023
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

Stanford Intelligent and Interactive Autonomous Systems Group 57 Dec 28, 2022
FairMOT - A simple baseline for one-shot multi-object tracking

FairMOT - A simple baseline for one-shot multi-object tracking

Yifu Zhang 3.6k Jan 08, 2023
End-to-end face detection, cropping, norm estimation, and landmark detection in a single onnx model

onnx-facial-lmk-detector End-to-end face detection, cropping, norm estimation, and landmark detection in a single onnx model, model.onnx. Demo You can

atksh 42 Dec 30, 2022
A 1.3B text-to-image generation model trained on 14 million image-text pairs

minDALL-E on Conceptual Captions minDALL-E, named after minGPT, is a 1.3B text-to-image generation model trained on 14 million image-text pairs for no

Kakao Brain 604 Dec 14, 2022
A PyTorch-based Semi-Supervised Learning (SSL) Codebase for Pixel-wise (Pixel) Vision Tasks

PixelSSL is a PyTorch-based semi-supervised learning (SSL) codebase for pixel-wise (Pixel) vision tasks. The purpose of this project is to promote the

Zhanghan Ke 255 Dec 11, 2022
The official homepage of the COCO-Stuff dataset.

The COCO-Stuff dataset Holger Caesar, Jasper Uijlings, Vittorio Ferrari Welcome to official homepage of the COCO-Stuff [1] dataset. COCO-Stuff augment

Holger Caesar 715 Dec 31, 2022
Custom implementation of Corrleation Module

Pytorch Correlation module this is a custom C++/Cuda implementation of Correlation module, used e.g. in FlowNetC This tutorial was used as a basis for

Clément Pinard 361 Dec 12, 2022
The implementation of ICASSP 2020 paper "Pixel-level self-paced learning for super-resolution"

Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti

Elon Lin 41 Dec 15, 2022
Fluency ENhanced Sentence-bert Evaluation (FENSE), metric for audio caption evaluation. And Benchmark dataset AudioCaps-Eval, Clotho-Eval.

FENSE The metric, Fluency ENhanced Sentence-bert Evaluation (FENSE), for audio caption evaluation, proposed in the paper "Can Audio Captions Be Evalua

Zhiling Zhang 13 Dec 23, 2022
Website for D2C paper

D2C This is the repository that contains source code for the D2C Website. If you find D2C useful for your work please cite: @article{sinha2021d2c au

1 Oct 21, 2021