< Master Python Data Science and Machine Learning Classification Techniques

83 casts | 16:09:09 for the total course

created by Mammoth Interactive INC

• 1. Python Language Basics
  • 00. Introduction
  • 01. Intro To Python

  • 02. Type Conversion Examples

  • 03. Operators

  • 04. Collections

  • 05. List Examples

  • 06. Tuples Examples

  • 07. Dictionaries Examples

  • 08. Ranges Examples

  • 09. Conditionals

  • 10. If Statement Examples

  • 11. Loops

  • 12. Functions

  • 13. Parameters And Return Values Examples

  • 14. Classes And Objects

  • 15. Inheritance Examples

  • 16. Static Members Examples

  • 17. Summary And Outro

• 2. Numpy 2020

  • 00. Course Intro | 2020 Numpy

  • 01. Intro To Numpy | 2020 Numpy

  • 02. Installing Numpy

  • 03. Creating Numpy Arrays

  • 04. Creating Numpy Matrices

  • 05. Getting And Setting Numpy Elements | 2020 Numpy

  • 06. Arithmetic Operations On Numpy Arrays | 2020 Numpy

  • 07. Numpy Functions Part 1 | 2020 Numpy

  • 08. Numpy Functions Part 2 | 2020 Numpy

  • 09. Summary And Outro | 2020 Numpy

• 3. Pandas 2020

  • 00. Panda Course Introduction

  • 01. Intro To Pandas

  • 02. Installing Pandas

  • 03. Creating Pandas Series

  • 04. Date Ranges

  • 05. Getting Elements From Series

  • 06. Getting Properties Of Series

  • 07. Modifying Series

  • 08. Operations On Series

  • 09. Creating Pandas Dataframes

  • 10. Getting Elements From Dataframes

  • 11. Getting Properties From Dataframes

  • 12. Dataframe Modification

  • 13. Dataframe Operations

  • 14 Dataframe Comparisons And Iteration

  • 15. Reading CSVs

  • 16. Summary And Outro

• 4. PyPlot 2020

  • 00. Course Intro | 2020 Pyplot

  • 01. Intro To Pyplot | 2020 Pyplot

  • 02. Installing Matplotlib | 2020 Pyplot

  • 03. Basic Line Plot | 2020 Pyplot

  • 04. Customizing Graphs | 2020 Pyplot

  • 05. Plotting Multiple Datasets | 2020 Pyplot

  • 06. Bar Chart | 2020 Pyplot

  • 07. Pie Chart | 2020 Pyplot

  • 08. Histogram | 2020 Pyplot

  • 09. 3D Plotting | 2020 Pyplot

  • 10. Course Outro | 2020 Pyplot

• 5. Machine Learning Theory 2020

  • 00. Course Intro | 2020 ML Theory

  • 01. Quick Intro To Machine Learning | 2020 ML Theory

  • 02. Deep Dive Into Machine Learning | 2020 ML Theory

  • 03. Problems Solved With Machine Learning Part 1 | 2020 ML Theory

  • 04. Problems Solved With Machine Learning Part 2 | 2020 ML Theory

  • 05. Types Of Machine Learning | 2020 ML Theory

  • 06. How Machine Learning Works | 2020 ML Theory

  • 07. Common Machine Learning Structures | 2020 ML Theory

  • 08. Steps To Build A Machine Learning Program | 2020 ML Theory

  • 09. Summary And Outro | 2020 ML Theory

• 6. Intro to Tensorflow 2020

  • 00. Course Intro | 2020 Intro to Tensorflow

  • 01. Intro To Tensorflow | 2020 Intro to Tensorflow

  • 02. Installing Tensorflow | 2020 Intro to Tensorflow

  • 03. Intro To Linear Regression | 2020 Intro to Tensorflow

  • 04. Linear Regression Model - Creating Dataset | 2020 Intro to Tensorflow

  • 05. Linear Regression Model - Building The Model | 2020 Intro to Tensorflow

  • 06. Linear Regression Model - Creating A Loss Function | 2020 Intro to Tensorflow

  • 07. Linear Regression Model - Training The Model | 2020 Intro to Tensorflow

  • 08. Linear Regression Model - Testing The Model | 2020 Intro to Tensorflow

• 7. Review Sentiment Analysis

  • 00. Course Intro | 2020 Review Sentiment Analysis

  • 01. How Machines Interpret Text | 2020 Review Sentiment Analysis

  • 02. Building The Model Part 1 - Examining Dataset | 2020 Review Sentiment Analysis

  • 03. Building The Model Part 2 - Formatting Dataset | 2020 Review Sentiment Analysis

  • 04. Building The Model Part 3 - Building The Model | 2020 Review Sentiment Analysis

  • 05. Building The Model Part 4 - Training The Model | 2020 Review Sentiment Analysis

  • 06. Building The Model Part 5 - Testing The Model.Mp4 | 2020 Review Sentiment Analysis

  • 07. Course Summary And Outro | 2020 Review Sentiment Analysis