The Top 5 Machine Learning Libraries in Python

The Top 5 Machine Learning Libraries in Python, available at Free, has an average rating of 4.17, with 33 lectures, 6 quizzes, based on 4279 reviews, and has 107282 subscribers.

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You will learn about Youll receive the completely annotated Jupyter Notebook used in the course. Youll be able to define and give examples of the top libraries in Python used to build real world predictive models. You will be able to create models with the most powerful language for machine learning there is. Youll understand the supervised predictive modeling process and learn the core vernacular at a high level. This course is ideal for individuals who are If youre looking to learn machine learning then this course is for you. It is particularly useful for If youre looking to learn machine learning then this course is for you. .

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Summary

Title: The Top 5 Machine Learning Libraries in Python

Price: Free

Average Rating: 4.17

Number of Lectures: 33

Number of Quizzes: 6

Number of Published Lectures: 32

Number of Published Quizzes: 6

Number of Curriculum Items: 39

Number of Published Curriculum Objects: 38

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Youll receive the completely annotated Jupyter Notebook used in the course.

Youll be able to define and give examples of the top libraries in Python used to build real world predictive models.

You will be able to create models with the most powerful language for machine learning there is.

Youll understand the supervised predictive modeling process and learn the core vernacular at a high level.

Who Should Attend

If youre looking to learn machine learning then this course is for you.

Target Audiences

If youre looking to learn machine learning then this course is for you.

Recent?Review from Similar Course:

“This was one of the most useful classes I have taken in a long time. Very specific, real-world examples. It covered several instances of ‘what is happening’, ‘what it means’ and ‘how you fix it’. I was impressed.” ?Steve

Welcome to The Top 5 Machine Learning Libraries in Python.? This is an introductory course on the process of building supervised machine learning models and then using libraries?in a computer programming language called Python.

What’s the top career in the world? Doctor? Lawyer? Teacher? Nope. None of those.

The top career in the world is the data scientist. Great. What’s a data scientist?

The area of study which involves extracting knowledge from data is called Data Science and people practicingin this field are called as Data Scientists.

Business generate a huge amount of data.?The data has tremendous value but there so much of it where do you begin to look for value that is actionable? That’s where the data scientist comes in.? The job of the data scientist is to create predictive models that can find hidden patterns in data that will give the business a competitive advantage in their space.

Don’t I need a PhD? ?Nope. Some data scientists do have PhDs but it’s not a requirement.? A similar career to that of the data scientist is the machine learning engineer.

A machine learning engineer is a person who builds predictive models, scores them and then puts them into production so that others in the company can consume or use their model. ?They are usually skilled programmers that have a solid background in data mining or other data related professions and they have learned predictive modeling.

In the course we are going to take a look at what machine learning engineers do. We are going to learn about the process of building supervised predictive models and build several using the most widely used programming language for machine learning. Python. There are literally hundreds of librarieswe can import into Python that are machine learning related.

A libraryis simply a group of code that lives outside the core language. We “import it” into our work space when we need to use its functionality. We can mix and match these libraries like Lego blocks.

Thanks for your interest in the The Top 5 Machine Learning Libraries in Pythonand we will see you in the course.?

Course Curriculum

Chapter 1: Introduction

Lecture 1: Whats the Course About? What will I Learn?

Lecture 2: Instructor Q & A

Lecture 3: Machine Learning Vernacular

Lecture 4: Must Know Terms Quiz

Lecture 5: The Machine Modeling Process

Lecture 6: Installing Python 3.X

Lecture 7: Jupyter Notebook Anatomy

Lecture 8: Course Downloads

Lecture 9: Summary

Chapter 2: Pandas

Lecture 1: Import Pandas and Manipulate Data

Lecture 2: Importing a CSV in Pandas

Lecture 3: Remove Columns and Sort Some Data

Lecture 4: Learning Tip

Lecture 5: Summary

Chapter 3: NumPy

Lecture 1: Anatomy of an Array

Lecture 2: Creating Arrays

Lecture 3: Accessing Elements in Our Array

Lecture 4: Summary

Chapter 4: SciKit-Learn

Lecture 1: What is SciKit-Learn?

Lecture 2: Data Sets

Lecture 3: An End to End Model

Lecture 4: Anatomy of an End to End Model

Lecture 5: What Does Accuracy Mean?

Lecture 6: Summary

Chapter 5: matplotlib

Lecture 1: The line and Scatter Plot

Lecture 2: The Histogram

Lecture 3: Summary

Chapter 6: NLTK

Lecture 1: What is NLP and NTLK?

Lecture 2: What is Tokenization?

Lecture 3: Word and Sentence Tokenization

Lecture 4: Summary

Lecture 5: Bonus Lecture: Tons of Free Real-World Machine Learning Content

Instructors

Mike West
Creator of LogikBot

Rating Distribution

1 stars: 86 votes

2 stars: 172 votes

3 stars: 757 votes

4 stars: 1694 votes

5 stars: 1570 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!