Download Complete Machine Learning & Data Science with Python

Complete Machine Learning & Data Science with Python


Complete Machine Learning & Data Science with Python | AZ is a zero-to-hundred machine learning and data science training course with Python programming language published by Udemy Academy. Python is a high-level and multi-purpose language that is used in various fields such as artificial intelligence, machine learning, data analysis, etc. Based on the Python programming language, many libraries have been developed such as Scikit, NumPy, Pandas, Matplotlib and Seaborn, each of which is used in different fields such as data analysis and visualization. Machine learning is an emerging and revolutionary technology that we have seen simple and practical examples of in Auto-Correct, predictive text and voice recognition capabilities. This technology is developing day by day and has opened its feet to various industries and platforms such as computer games, digital marketing, programming, etc.

Intelligent virtual assistants such as Alexa and Siri in Amazon and Apple products use machine learning algorithms and mathematical models. It is predicted that there will be around 11.5 million job vacancies in data science and machine learning by 2026, which promises a bright future for these modern technologies. Machine learning-based systems are a set of intelligent and decision-making systems that train and train a specific mathematical model based on real data and then can make decisions in new situations and provide effective predictions. For example, to build a face recognition system, in the first step, we enter a large number of images and faces into the data model and the desired information. After reviewing the information, the system quickly recognizes patterns among the information and can make decisions in the future and in new situations fully automatically.

What is in the Complete Machine Learning & Data Science with Python course AZ you will learn:

  • Machine learning based systems and their applications and advantages
  • Specialized vocabulary of machine learning and data science
  • Measurement and evaluation criteria and models
  • statistical classification (Classification) and regression analysis
  • Development of machine learning based systems with Python
  • Supervised learning
  • Cross-Validation Method
  • Bias-Variance Tradeoff
  • Visualization and display of data in the form of graphic models with Matplotlib and seaborn libraries
  • Machine learning with SciKit
  • Linear Regression Theory
  • Logistic Regression Theory
  • K Nearest Neighbors Algorithm
  • Decision Trees
  • Random Forest Algorithm
  • Support Vector Machines Algorithm
  • K Means Clustering Algorithm
  • Hierarchical Clustering Algorithm
  • Principal Component Analysis
  • Recommender System
  • Python programming language syntax
  • Other uses of the Python programming language

Course details

Publisher: Yudmi
teacher: Oak Academy
English language
Training level: introductory to advanced
Number of courses: 46
Training duration: 8 hours and 43 minutes

Course topics on 11/2021

Prerequisites of the Complete Machine Learning & Data Science with Python course AZ

Basic knowledge of Python Programming Language

Be Able To Operate & Install Software On A Computer

Free software and tools used during the machine learning az course

Determination to learn machine learning and patience.

Motivation to learn the second largest number of job postings relative program language among all others

Data visualization libraries in python such as seaborn, matplotlib

Curiosity for machine learning python

Desire to learn Python

Desire to work on python machine learning

Desire to learn matplotlib

Desire to learn pandas

Desire to learn numpy

Desire to work on seaborn

Desire to learn machine learning az, complete machine learning

Course images

Complete Machine Learning & Data Science with Python |  AZ

Video introducing the Complete Machine Learning & Data Science with Python course AZ

Installation guide

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Quality: 720p

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Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 848 MB

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