Table of Contents

• Free Books

  • R Programming for Data Science
  • Mathematics for Machine Learning
  • Pengenalan Pembelajaran Mesin dan Deep Learning (Bahasa Indonesia)
  • Bayesian Reasoning and Machine Learning
  • Interpretable Machine Learning
  • Python Data Science Handbook
  • Bayesian Reasoning and Machine Learning

• Courses

  • Practical Deep Learning for Coders
  • Machine Learning
  • Applied Machine Learning in Python
  • Machine Learning with Big Data
  • Principles of Machine Learning
  • Machine Learning for Data Science and Analytics

• Datasets

  • Kaggle Datasets
  • Machine Learning Datasets Repository
  • Indonesia Family Life Survey
  • UCI Machine Learning Repository
  • IMDb Datasets
  • Caption Contest Data

• Sample Code

  • Introducing Data Science
  • Deep Learning with PyTorch (Bahasa Indonesia)
  • Data Science From Scratch
  • Data Science with Python (Bahasa Indonesia)
  • Practical Machine Learning with Python
  • Machine Learning with R
  • Practical Data Science Cookbook

• Videos and Lectures

  • Machine Learning by Andrew Ng
  • Intro to Machine Learning by Eric Grimson
  • Machine Learning Course - CS 156
  • Machine Learning from Scratch using Python
  • Gaussian Mixture Models - The Math of Intelligence (Week 7)
  • Machine Learning and Data Mining Short Series for Beginner (UC Irvine)
  • Complete Tutorial of Apache Spark (Beginner - Intermediate)
  • Machine Learning by Andrew Ng
  • Machine Learning Course - CS 156
  • Machine Learning from Scratch using Python
  • Gaussian Mixture Models - The Math of Intelligence (Week 7)
  • Machine Learning and Data Mining Short Series for Beginner (UC Irvine)
  • Complete Tutorial of Apache Spark (Beginner - Intermediate)

• Papers

  • Local algorithms for interactive clustering
  • On Perturbed Proximal Gradient Algorithms
  • Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
  • Nearly optimal classification for semimetrics
  • A Bayesian Framework for Learning Rule Sets for Interpretable Classification
  • Local algorithms for interactive clustering
  • On Perturbed Proximal Gradient Algorithms
  • Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
  • Nearly optimal classification for semimetrics
  • A Bayesian Framework for Learning Rule Sets for Interpretable Classification

• Tutorials

  • A Simple Approach to Predicting Customer Churn
  • Complete Guide to Topic Modeling
  • K-Means Clustering in Python
  • How To Implement Naive Bayes From Scratch in Python
  • Twitter Sentiment Analysis with NLTK
  • Complete Guide to Topic Modeling

• Conferences (Mostly in Indonesia)

  • Seminar Nasional Sistem Informasi
  • International Seminar on Intelligence Technology and Its Application
  • International Conference on Advanced Computer Science and Information Systems
  • International Conference on Science in Information Technology
  • International Conference on Soft Computing, Intelligent Systems, and Information Technology
  • International Conference on Data and Information Science
  • 2019 International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)
  • International Conference on Signals and Systems
  • Seminar Nasional Sistem Informasi
  • International Seminar on Intelligence Technology and Its Application
  • International Conference on Advanced Computer Science and Information Systems
  • 2019 International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)
  • International Conference on Signals and Systems

• Libraries

  • spaCy
  • XGBoost
  • CNTK
  • Scikit-learn
  • Natural Language Toolkit