Machine Learning with Python Foundations - DeepNeuron

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Course Content

Total learning: 24 lessons Time: 10 weeks

1. Introduction 0/3
- Lecture1.1
  
  What you should know
- Lecture1.2
  
  The tools you need
- Lecture1.3
  
  Using the exercise files
2. Machine Learning 0/6
- Lecture2.1
  
  What is machine learning?
- Lecture2.2
  
  What is not machine learning?
- Lecture2.3
  
  What is unsupervised learning?
- Lecture2.4
  
  What is supervised learning?
- Lecture2.5
  
  What is reinforcement learning?
- Lecture2.6
  
  What are the steps to machine learning?
3. Collecting Data for Machine Learning 0/2
- Lecture3.1
  
  Things to consider when collecting data
- Lecture3.2
  
  How to import data in Python
4. Understanding Data for Machine Learning 0/4
- Lecture4.1
  
  Describe your data
- Lecture4.2
  
  How to summarize data in Python
- Lecture4.3
  
  Visualize your data
- Lecture4.4
  
  How to visualize data in Python
5. Preparing Data for Machine Learning 0/7
- Lecture5.1
  
  Common data quality issues
- Lecture5.2
  
  How to resolve missing data in Python
- Lecture5.3
  
  Normalizing your data
- Lecture5.4
  
  How to normalize data in Python
- Lecture5.5
  
  Sampling your data
- Lecture5.6
  
  How to sample data in Python
- Lecture5.7
  
  Reducing the dimensionality of your data
6. Types of Machine Learning Models 0/2
- Lecture6.1
  
  Classification vs. regression problems
- Lecture6.2
  
  How to build a machine learning model in Python

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