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Practical Machine Learning: Build 25 Projects From Scratch

Practical Machine Learning Course: Learn To Build Machine Learning, Data Science Projects & Case Studies With Python
2.9
2.9/5
(26 reviews)
888 students
Created by

8.4

CourseMarks Score®

9.9

Freshness

5.0

Feedback

9.8

Content

Platform: Udemy
Video: 16h 2m
Language: English
Next start: On Demand

Top Data Science courses:

Detailed Analysis

CourseMarks Score®

8.4 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.9 / 10
This course was last updated on 11/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

5.0 / 10
We analyzed factors such as the rating (2.9/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.8 / 10
Video Score: 10.0 / 10
The course includes 16h 2m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 9.4 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

25 articles.
28 resources.
0 exercise.
0 test.

Table of contents

Description

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.
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.

You will learn

✓ Build Best Performing Machine Learning Models
✓ Have a great intuition of many data science models
✓ Learn how to build data science models
✓ Learn how to use Scikit-learn to apply powerful machine learning algorithms.
✓ Make robust data science models
✓ How to improve your Machine Learning Models
✓ Create supervised machine learning algorithms to predict classes.
✓ Learn best practices for real-world data sets.

Requirements

• Knowledge of data science

This course is for

• Beginners in data science

How much does the Practical Machine Learning: Build 25 Projects From Scratch course cost? Is it worth it?

The course costs $12.99. And currently there is a 35% discount on the original price of the course, which was $19.99. So you save $7 if you enroll the course now.

Does the Practical Machine Learning: Build 25 Projects From Scratch course have a money back guarantee or refund policy?

YES, Practical Machine Learning: Build 25 Projects From Scratch has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Practical Machine Learning: Build 25 Projects From Scratch course, but there is a $7 discount from the original price ($19.99). So the current price is just $12.99.

Who is the instructor? Is TheMachineLearning.Org . a SCAM or a TRUSTED instructor?

TheMachineLearning.Org . has created 13 courses that got 768 reviews which are generally positive. TheMachineLearning.Org . has taught 56,827 students and received a 3.9 average review out of 768 reviews. Depending on the information available, TheMachineLearning.Org . is a TRUSTED instructor.
Machine Learning Engineer
TheMachineLearning. org mission is to make highly valuable career skills in machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you. TheMachineLearning. org leverages the power of cutting edge Artificial Intelligence to empower businesses to make massive profits by optimizing processes, maximizing efficiency and increasing profitability.

8.4

CourseMarks Score®

9.9

Freshness

5.0

Feedback

9.8

Content

Platform: Udemy
Video: 16h 2m
Language: English
Next start: On Demand

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