Practical Machine Learning with Python For Developers & Data Scientists

Main Speaker:

Tracks:

Cloud

Data

Seminar Categories:

Analytics

Cloud

Data

Course ID:

42247

Date:

26.11.2020

Daily seminar
9:00-16:30
Live Digital Sessions

Overview

Python is a common 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

Who Should Attend

  • Developers
  • Data Scientists

Prerequisites

The participants should have some knowledge with python language.

Course Contents

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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