Practical Machine Learning with Python For Developers & Data Scientists

Practical Machine Learning with Python For Developers & Data Scientists

Main Speaker:


Liran Ben Haim

Tracks:

Code
Data

Seminar Categories:

Backend
BI & ML
Code
Data

Course ID:

43664

Date:

23.6.2019

Time:

Daily seminar
9:00-16:30

43664

Overview

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

Prerequisites

The participants should have some knowledge with python language

Course Contents

Overview

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



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