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Practical Machine Learning with Python

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Course ID:

44160

Time:

Daily seminar
9:00-16:30
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 The participants should have some knowledge with python language Topics: 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
Batch vs Online Learning Instance vs model based learing Variables and features Deep Learning overview Classification Regressions Types of Data Data preparation and cleaning Data visualization Missing values Scikit Learn Linear Regression Logistic Regression Support vector machines Decision trees and random forests Naïve Bayes KNN NLP More ML Algorithms Other tools and libraries  


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