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Machine Learning

Machine learning is is the kind of programming which gives computers the capability to automatically learn from data without being explicitly programmed. This means in other words that these programs change their behaviour by learning from data.

We will cover various aspects of machine learning in this course. Of course, everything will be related to Python. So it is Machine Learning by using Python. What is the best programming language for machine learning? Python is clearly one of the top players!

This training is based on 100% hands on with real time scenarios.

In this course, We cover following topics:

- Introduction in Machine Learning with Python
- Machine Learning Terminology
- Evaluation Metrics
- Data Representation and Visualization of Data
- Data, Splitting in Learn and Test Data
- Articial Datasets with Scikit-Learn
- k-nearest Neighbor Classifier
- Neural Networks Introduction
- Separating Classes with Dividing Lines
- Simple Neural Network from Scratch Using Python
- Initializing the Structure and the Weights of a Neural Network
- Running Neural Network in Python
- Backpropagation in Neural Networks
- Training a Neural Network with Python
- Softmax as Activation Function
- Confusion Matrix
- Training and Testing with MNIST
- Dropout Neural Networks
- Neural Networks with Scikit
- Machine Learning with Scikit and Python
- Introduction Naive Bayes Classifier
- Naive Bayes Classifier with Scikit
- Introduction into Text Classification using Naive Bayes
- Python Implementation of Text Classification
- Natural Language Processing: Encoding and classifying Text
- Natural Language Processing: Examples
- Decision Trees
- Regression Trees
- Random Forests
- Boosting Algorithm
- Principal Component Analysis
- Linear Discriminant Analysis
- Expectation Maximization and Gaussian Mixture Model
- Introduction into TensorFlow