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Home Programming

28 Real World Data Science & Machine Learning Projects 2022

March 13, 2022
in Programming, Free Course, Tutorials
28 Real World Data Science & Machine Learning Projects 2022

28 Real World Data Science & Machine Learning Projects 2022

This Asset we are sharing with you the 28 Real World Data Science & Machine Learning Projects 2022 free download links. On our website, you will find lots of premium assets free like Free Courses, Photoshop Mockups, Lightroom Preset, Photoshop Actions, Brushes & Gradient, Videohive After Effect Templates, Fonts, Luts, Sounds, 3d models, Plugins, and much more. Psdly.com is a free graphics content provider website that helps beginner graphic designers as well as freelancers who can’t afford high-cost courses and other things.

File Name:28 Real World Data Science & Machine Learning Projects 2022
Content Source:https://www.udemy.com/course/build-real-world-machine-learning-projects
Genre / Category:Programming
File Size :10.2GB
Publisher:udemy
Updated and Published:March 13, 2022
Product Details

What you’ll learn: 

Learn to use NumPy for Numerical Data

Learn to use Pandas for Data Analysis

Clean your input data to remove outliers

Master Machine Learning and use it on the job

Learn how to use Scikit-learn to apply powerful machine learning algorithms.

Create supervised machine learning algorithms to predict classes.

Requirements:

Basic knowledge of machine learning

Description:

Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to self-learn and improve over time without being explicitly programmed. In short, machine learning algorithms are able to detect and learn from patterns in data and make their own predictions.

In traditional programming, someone writes a series of instructions so that a computer can transform input data into a desired output. Instructions are mostly based on an IF-THEN structure: when certain conditions are met, the program executes a specific action.

Machine learning, on the other hand, is an automated process that enables machines to solve problems and take actions based on past observations.

Basically, the machine learning process includes these stages:

Feed a machine learning algorithm examples of input data and a series of expected tags for that input.

The input data is transformed into text vectors, an array of numbers that represent different data features.

Algorithms learn to associate feature vectors with tags based on manually tagged samples, and automatically makes predictions when processing unseen data.

While artificial intelligence and machine learning are often used interchangeably, they are two different concepts. AI is the broader concept – machines making decisions, learning new skills, and solving problems in a similar way to humans – whereas machine learning is a subset of AI that enables intelligent systems to autonomously learn new things from data.Who this course is for:Beginners in machine learning

Who this course is for:

Beginners in machine learning

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DOWNLOAD LINK: 28 Real World Data Science & Machine Learning Projects 2022

build-real-world-machine-learning-projects.part1.rar – 6.0 GB
build-real-world-machine-learning-projects.part2.rar – 4.2 GB

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