AtefeMsb
Software Engineer - Machine learning Engineer - Founder of Gilgamesh Inc. - Santa Clara University Graduate
Gilgamesh IncSan Francisco, ca
AtefeMsb's Stars
getify/You-Dont-Know-JS
A book series on JavaScript. @YDKJS on twitter.
wsargent/docker-cheat-sheet
Docker Cheat Sheet
john-smilga/node-express-course
fastapi/fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
AtefeMsb/LeetCode
My Interview Preparation Journey in JAVA
patrickloeber/MLfromscratch
Machine Learning algorithm implementations from scratch.
ritvikmath/YouTubeVideoCode
Code related to my YouTube vids!
Sroy20/machine-learning-interview-questions
This repository is to prepare for Machine Learning interviews.
AtefeMsb/Machine-Learning-Engineer-Nanodegree
class notes and project from my Udacity machine learning engineer degree.
aws/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
udacity/deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
amanchadha/coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
jwasham/coding-interview-university
A complete computer science study plan to become a software engineer.
bentrevett/pytorch-sentiment-analysis
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
xizhengszhang/Leetcode_company_frequency
Collection of leetcode company tag problems. Periodically updating.
checkcheckzz/system-design-interview
System design interview for IT companies
williamfiset/Algorithms
A collection of algorithms and data structures
remicnrd/ml_cheatsheet
A 5-pages only Machine Learning cheatsheet focusing on the most popular algorithms under the hood
khangich/machine-learning-interview
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
fastai/fastai_dev
fast.ai early development experiments
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
DreamOfTheRedChamber/think-bigger
Everything except technical details
3b1b/manim
Animation engine for explanatory math videos
mnielsen/neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
google/guava
Google core libraries for Java
data-science-on-aws/data-science-on-aws
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
udacity/sagemaker-deployment
Code and associated files for the deploying ML models within AWS SageMaker
mission-peace/interview
Interview questions
MarcDiethelm/contributing
How to make a clean pull request on Github