Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

Slide : In Defense of Smart Algorithms over Hardware Acceleration for Large-scale Deep Learning Systems

Hash Your Way To a Better Neural Network

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

The picture comes from Machine Learning Algorithms Mindmap.

Feature Engineering

Handling Categorical Variables in Machine Learning

Regularization in Machine Learning Models

Ensemble

Frameworks

Libraries for Gradient Boosting

Big-data (Spark) Friendly Frameworks …

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

https://towardsdatascience.com/automatic-feature-engineering-using-deep-learning-and-bayesian-inference-application-to-computer-7b2bb8dc7351

Feature selection Feature extraction Adding features through domain expertise

FeatureTools a Python library for feature engineering Deep neural network can extract features too

whether feature engineering is …

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

Methodology

hyper-parameter tuning, grid search bayesian optimization evolutionary algorithms genetic programming cross validation k-fold Neural Architecture Search with Reinforcement Learning

Libraries

Optuna

auto-sklearn

Ludwig

Ludwig is a toolbox that allows to …

** Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

Reinforcement Learning algorithms — an intuitive overview has a good overview of different approaches to RL. **

Courses & Tutorials

http://rail.eecs.berkeley.edu/deeprlcourse/

https://towardsdatascience.com/reinforcement-learning-q-learning-with-decision-trees-ecb1215d9131

Frameworks

The article A …