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

NeuralProphet: A simple forecasting package

Hands-on demonstrations for data scientists exploring Amazon SageMaker

A repo for the book 'Streamlit for Data Science' by Tyler Richards

MIDI to MML Converter

Deep Reinforcement Learning in Pac-man

Distributed Asynchronous Hyperparameter Optimization in Python

nannyml: post-deployment data science in python

Solving the Traveling Salesman Problem using Self-Organizing Maps

10 Weeks, 20 Lessons, Data Science for All!

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Demo of using the Nutter for testing of Databricks notebooks in the CI/CD pipeline

Version 1 of Technical Best Practices of Azure Databricks based on real world Customer and Technical SME inputs

COVID-19 Projections Using Machine Learning

Uplift modeling and causal inference with machine learning algorithms

Scaleogram plot for Continuous Wavelet Transform made easy

This is Andrew NG Coursera Handwritten Notes.

The goal of CLAIMED is to enable low-code/no-code rapid prototyping style programming to seamlessly CI/CD into production.

Data Science Learning Path - A complete guide to learn data science for beginners

Supplementary material for the article "Combining Static and Dynamic Features for Multivariate Sequence Classification"

Plotting Assignment 1 for Exploratory Data Analysis

code and sessions for articles on joyofdata.de

Python tutorials in both Jupyter Notebook and youtube format.

Kumpulan materi "Melek For Member"