ankit-kothari
I am very passionate about data science . I have developed strong skills in Python, Pytorch, Tensorflow, Keras, SQL, Hive, Github, Pyspark, docker, Sklearn.
Oracle AmericaAshburn, Virginia
ankit-kothari's Stars
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
github/copilot-docs
Documentation for GitHub Copilot
alexeygrigorev/data-science-interviews
Data science interview questions and answers
jessevig/bertviz
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
mshumer/gpt-llm-trainer
eon01/DockerCheatSheet
🐋 Docker Cheat Sheet 🐋
dair-ai/ML-Notebooks
:fire: Machine Learning Notebooks
ericmjl/bayesian-stats-modelling-tutorial
How to do Bayesian statistical modelling using numpy and PyMC3
amitkaps/recommendation
Recommendation System using ML and DL
empathy87/storytelling-with-data
Plots from the book "Storytelling with data" implementation using Python and matplotlib
fonnesbeck/scipy2014_tutorial
Tutorial: Bayesian Statistical Analysis in Python
xei/recommender-system-tutorial
A step-by-step tutorial on developing a practical recommendation system (retrieval and ranking) using TensorFlow Recommenders and Keras.
EcZachly/video-game-training-sql
Hey this is the repo that has all the queries and data for my video game training series!
smilli/kneser-ney
Kneser-Ney implementation in Python
LoryPack/BPMF
Python implementation of Bayesian Probabilistic matrix Factorization algorithm.
tdubon/study_notes
Repo contains Jupyter notebooks compiled during my review of the programming books listed.
coiled/dask-mini-tutorial
This repo contains a short version of a dask tutorial.
ankit-kothari/30DayChartChallenge_Collection2021
Collection of contributions to and resources for the first #30DayChartChallenge in April 2021
ankit-kothari/ML-foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science