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Deep Learning Prerequisites: The Numpy Stack in Python V2

Deep Learning Prerequisites: The Numpy Stack in Python V2

NumpyScipy, Pandas, and Matplotlib: prep for deep learningmachine learning, and artificial intelligence - Free Course.

What you'll learn

  • Basic operations in Numpy, Scipy, Pandas, and Matplotlib
  • Vector, Matrix, and Tensor manipulation
  • Visualizing data
  • Reading, writing, and manipulating DataFrames


  • Linear Algebra, Probability, and Python Programming


Welcome! This is Deep Learning, Machine Learning, and Data Science Prerequisites: The Numpy Stack in Python (V2).

The reason I made this course is because there is a huge gap for many students between machine learning "theory" and writing actual code. Deep Learning: Artificial Neural Network

As I've always said: "If you can't implement it, then you don't understand it".

Without basic knowledge of data manipulation, vectors, and matrices, students are not able to put their great ideas into working form, on a computer.

This course closes that gap by teaching you all the basic operations you need for implementing machine learning and deep learning algorithms.

The goal is that, after you take this course, you will learn about machine learning algorithms, and implement those algorithms in code using the tools and techniques you learned in this course. Master Deep Learning | A Step-by-Step Guide for 2021

Suggested Prerequisites:

  • linear algebra
  • probability
  • Python programming

Who this course is for:

  • Anyone who wants to implement Machine Learning algorithms

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