groverpr

Machine-Learning

Notes for machine learning

learn_python_libraries

Exploring most useful libraries of Python. Each notebook covers basic and advanced functionalities of a python library.

deep-learning

Linear-Algebra

fastai

The fast.ai deep learning library, lessons, and tutorials

ml_wrappers

Functions/ Wrappers around Sklearn, Pandas, Numpy for easier and faster Machine Learning

amazon-sagemaker-notebook-instance-lifecycle-config-samples

A collection of sample scripts to customize Amazon SageMaker Notebook Instances using Lifecycle Configurations

automl_multimodal_benchmark

Repository for Multimodal AutoML Benchmark

aws-fraud-detector-samples

Sample code and datasets for Amazon Fraud Detector

beir

A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

data_challenges

Solutions to data challenges

datasets

Different datasets for experiments

deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

docker-python

Kaggle Python docker image

fast_template

A template for really easy blogging with GitHub Pages

github-readme-stats

:zap: Dynamically generated stats for your github readmes

groverpr.github.io

My ML blog

learning-deep

All my deep learning notes

lolviz

A simple Python data-structure visualization tool for lists of lists, lists, dictionaries; primarily for use in Jupyter notebooks / presentations

markdown_readme

Markdown - you can mark up titles, lists, tables, etc., in a much cleaner, readable and accurate way if you do it with HTML.

ml-algos-from-scratch

Implementation of commonly used ML algorithms form scratch

ML-Papers-Intuitions

Simple explanations of ML research papers

msan501

Course notes for MSAN501, computational boot camp, at the University of San Francisco

msan692

MSAN692 Data Acquisition

nbdev

Create delightful python projects using Jupyter Notebooks

papers-we-love

Papers from the computer science community to read and discuss.

python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.