maykulkarni's Stars
github/gitignore
A collection of useful .gitignore templates
3b1b/manim
Animation engine for explanatory math videos
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
hindupuravinash/the-gan-zoo
A list of all named GANs!
vdumoulin/conv_arithmetic
A technical report on convolution arithmetic in the context of deep learning
iterative/dvc
🦉 ML Experiments and Data Management with Git
nltk/nltk
NLTK Source
soumith/ganhacks
starter from "How to Train a GAN?" at NIPS2016
cs231n/cs231n.github.io
Public facing notes page
amueller/introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
xingyizhou/CenterNet
Object detection, 3D detection, and pose estimation using center point detection:
soumith/convnet-benchmarks
Easy benchmarking of all publicly accessible implementations of convnets
microsoft/DialoGPT
Large-scale pretraining for dialogue
kaleko/CourseraML
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!
flexdinesh/dev-landing-page
Minimal landing page for developers
iskandr/fancyimpute
Multivariate imputation and matrix completion algorithms implemented in Python
RedaOps/ann-visualizer
A python library for visualizing Artificial Neural Networks (ANN)
GKalliatakis/Delving-deep-into-GANs
Generative Adversarial Networks (GANs) resources sorted by citations
osh/KerasGAN
A couple of simple GANs in Keras
azsk/DevOpsKit-docs
maykulkarni/Machine-Learning-Notebooks
Machine Learning notebooks for refreshing concepts.
jnothman/UpSetPlot
Draw UpSet plots with Matplotlib
azsk/DevOpsKit
lightforever/mlcomp
Distributed DAG (Directed acyclic graph) framework for machine learning with UI
distillpub/post--visual-exploration-gaussian-processes
A Visual Exploration of Gaussian Processes
chrisjmccormick/wiki-sim-search
Similarity search on Wikipedia using gensim in Python.
alekseynp/kaggle-dev-ops
glemaitre/glemaitre.github.io
Personal webpage
maykulkarni/Manhattan-GRE-Words-Shuffled
nimitpattanasri/mlxai.github.io
I am looking for opportunity and challenge where I can develop and apply my skills in machine learning and data visualization. Now I enjoy every single day studying deep learning from great courses, Stanford's CS231n and Stanford's CS224d. I blog my experience at https://mlxai.github.io