Machine Learning with Python Online Training

First Machine Learning Algorithm Python

• Various machine learning algorithms in Python
• Apply machine learning algorithms in Python

Feature Selection and Pre-processing

• How to select the right data
• Which are the best features to use
• Additional feature selection techniques
• A feature selection case study
• Preprocessing Introduction
• Preprocessing Scaling Techniques
• How to preprocess your data
• How to scale your data
• Feature Scaling Final Project

Which Algorithms Perform Best

• Highly efficient machine learning algorithms
• Bagging Decision Trees
• The power of ensembles
• Random Forest Ensemble technique
• Boosting – Adaboost
• Boosting ensemble stochastic gradient boosting
• A final ensemble technique

Model Selection Cross Validation Score

• Introduction Model Tuning
• Parameter Tuning GridSearchCV
• A second method to tune your algorithm
• How to automate machine learning
• Which ML algo should you choose
• How to compare machine learning algorithms in practice

Neural Networks and deep learning in Python

• Neural Networks introduction
• What is deep learning
• What is one hot encoding
• How to implement one hot encoding
• How to handle missing values
• How to impute missing values
• Introducing the MNIST dataset

Tensor Flow

• Programming a neural network in tensorflow
• Programming a neural network – multilayer perceptron in tensorflow

Keras

• Introduction to keras – a convient way to code neural networks
• What is a convolutional neural network
• How does a cnn work

CNN and RNNs

• Creating a convolutional neural network from scratch
• What are RNNs – Introduction to RNNs
• Recurrent Neural Networks rnn in python
• LSTMs for beginners – understanding LSTMs
• long short term memory neural networks lstm in python