Building Your First Classification Model in Python with Scikit-learn

Free Live ML Workshop #4 on Oct 1 - Register Now

Description

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).Read more.

This resource is offered by an affiliate partner. If you pay for training, we may earn a commission to support this site.

Career Relevance by Data Role

The techniques and tools covered in Algorithmic Toolbox are most similar to the requirements found in Data Scientist job advertisements.

Similarity Scores (Out of 100)