Books & Videos

Table of Contents

Chapter: Installation and Setup

The Course Overview

05m 47s

Python Installation

06m 28s

Chapter: Python

Overview of Python in Engineering and Scientific Computing

03m 20s

on and the IPython (now Jupiter) Notebook

06m 40s

Chapter: NumPy and its functionality

Working with NumPy Arrays

16m 52s

Avoiding For Loops in Some Mathematical Operations via NumPy Arrays

09m 48s

Matrices as an Efficient Way to Operate with Data

07m 55s

Implementation in NumPy of a Matrix Object and Some Operations

07m 19s

Functionality of NumPy for Reading and Writing Data

08m 54s

Chapter: SciPy and its Functionality

General Introduction to SciPy

07m 11s

Statistics with SciPy

10m 59s

Fitting Curves with the SciPy Library

06m 0s

Solving Ordinary Differential Equations with the SciPy Library

14m 14s

SciPy Library Special Functions

07m 13s

Chapter: Matplotlib

Two Dimensional Plots via Matplotlib (2D plots)

06m 35s

Three Dimensional Plots via Matplotlib (3D plots)

07m 27s

Scatter and Contour Plots via Matplotlib

05m 21s

Plotting Histograms via Matplotlib

03m 39s

Chapter: Data Preprocessing and Machine Learning Language

Generalities on Machine Learning

06m 19s

Generalities on Working with Data: Getting it and Putting it in the Right Format

04m 41s

Data Preprocessing and Exploration

05m 32s

Collapsing Data via Principal Component Analysis

09m 8s

Generalities of Supervised and Unsupervised Learning

05m 1s

Chapter: Solving the Regression Problem in Machine Learning Language

Overview of Optimization and the Gradient Descent Method

06m 3s

Gradient Descent Implementation via NumPy and Examples Comparing it with SciPy Functions for Optimization

08m 39s

The Linear Regression Problem and its Solution via Gradient Descent

07m 45s

Solving a Non-Linear Regression Problems via Gradient Descent and Some Thoughts for Improvements

08m 56s

Chapter: Logistic Classification

Overview of Logistic Regression for Classification and Prediction

06m 36s

Implementing Logistic Regression for Classification via SciPy Functions

07m 43s