From Grokking Artificial Intelligence Algorithms by Rishal Hurbans
What you’ll learn in this article:
§ The lifecycle of a genetic algorithm.
§ Designing and developing a genetic algorithm to solve problems.
§ The parameters for configuring a genetic algorithm lifecycle based on different scenarios, problems, and data sets.
From Grokking Artificial Intelligence Algorithms by Rishal Hurbans
From Data Science Bookcamp by Leonard Apeltsin
Six Questions for Jesse C. Daniel, author of Data Science with Python and Dask
Jesse Daniel is a software developer (Python, Scala, JavaScript, C#) who leads a team of data scientists at a media technology company. He has taught Python for Data Science at the University of Denver.
From Real-World Natural Language Processing by Masato Hagiwara
From Probabilistic Deep Learning with Python by Oliver Dürr, Beate Sick, and Elvis Murina
From Machine Learning for Business by Doug Hudgeon and Richard Nichol
This article covers basic time-series forecasting: what it is and why it’s a tough problem.
From Mastering Large Datasets with Python by J.T. Wolohan
This article covers
· Using map to do complex data transformations
· Chaining together small functions into pipelines
· Applying these pipelines in parallel on large datasets
From Probabilistic Deep Learning with Python by Oliver Dürr, Beate Sick, and Elvis Murina
This article dives into neural network architectures and how get started implementing and using them.