Python is a great programming language for data analysis and machine learning. With its packages and tools , writing a machine learning process with python is a very simple task.

In this seminar we will cover the important packages and tools and see some practical examples how we can use it to solve machine learning problems

• Developers
• Data Scientists

The participants should have some knowledge with python language

Important packages

• Numpy
• Matplotlib and seaborn
• Scipy and Scikits
• Pandas

Why Learn

Applications

Machine Learning Process

Learning Types:

• Supervised Learning
• Unsupervised Learning
• Semi-Supervised Learning
• Active Learning
• Reinforcement learning

Variables and features

Classification

Regressions

Types of Data

Data preparation and cleaning

Data visualization

Scikit Learn

Models:

• Linear Regression
• Logistic Regression
• Support vector machines
• Decision trees and random forests
• Naïve Bayes
• KNN

Deep Learning overview

Neural Networks

NLP