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ai-for-beginners

12 Weeks, 24 Lessons, AI for All!

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

apache-spark-2-data-processing-and-real-time-analytics

Master complex big data processing, stream analytics, and machine learning with Apache Spark

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-log-analysis

A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps

awesome-mlops

:sunglasses: A curated list of awesome MLOps tools

data-engineering-zoomcamp

Free Data Engineering course!

data-science-for-beginners

10 Weeks, 20 Lessons, Data Science for All!

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

ebookmlcb

ebook Machine Learning cơ bản

eng-edu

gcp-training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

graph-notebook

Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.

grokking_algorithms

Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

kafka-streams-master-class

learntosparkcode

loglizer

A log analysis toolkit for automated anomaly detection [ISSRE'16]

logparser

A toolkit for automated log parsing [ICSE'19, TDSC'18, DSN'16]

machine-learning-engineering-for-production-public

Public repo for DeepLearning.AI MLEP Specialization

machine-learning-interviews

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

machine-learning-with-python

Python code for common Machine Learning Algorithms

ml-design-patterns

Source code accompanying O'Reilly book: Machine Learning Design Patterns

ml-for-beginners

12 weeks, 25 lessons, 50 quizzes, classic Machine Learning for all

ml_water_potability_fastapi_deployment

ML model deployment using docker, kubernetes; API deployment with FastAPI; and MLOps using MLFlow for water potability dataset

mysql-exercises-with-sakila-db-

python

python-clustering-exercises

Jupyter Notebook exercises for k-means clustering with Python 3 and scikit-learn