Achieve your first Machine Learning project in Python in 2h
Achieve your first Machine Learning project in Python in 2h, available at $19.99, has an average rating of 4.33, with 25 lectures, based on 3 reviews, and has 24 subscribers.
You will learn about Become quickly operational in Machine Learning Get familiar with Python for Data Science Get a framework that can be applied to other Data Science projects Solve a concrete problem thanks to Machine Learning Discover algorithms commonly used in Machine Learning Understand the different challenges that a data scientist can encouter This course is ideal for individuals who are People starting in Machine Learning and Data Science who wish to be quickly operational It is particularly useful for People starting in Machine Learning and Data Science who wish to be quickly operational.
Enroll now: Achieve your first Machine Learning project in Python in 2h
Summary
Title: Achieve your first Machine Learning project in Python in 2h
Price: $19.99
Average Rating: 4.33
Number of Lectures: 25
Number of Published Lectures: 25
Number of Curriculum Items: 25
Number of Published Curriculum Objects: 25
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Become quickly operational in Machine Learning
- Get familiar with Python for Data Science
- Get a framework that can be applied to other Data Science projects
- Solve a concrete problem thanks to Machine Learning
- Discover algorithms commonly used in Machine Learning
- Understand the different challenges that a data scientist can encouter
Who Should Attend
- People starting in Machine Learning and Data Science who wish to be quickly operational
Target Audiences
- People starting in Machine Learning and Data Science who wish to be quickly operational
In just 2 hours you will be able to complete a Machine Learning project from start to finish.
You will know all the steps of a Data Science project and how to carry them out in Python.
So far you have probably learned a lot about the theory of Machine Learning but you have no idea how to apply it to real life cases.
You may want to incorporate Machine Learning into your professional projects to improve your results but this seems overwhelming.
If you keep going like this, you can continue to learn about Machine Learning without going into practice and lose a lot of time. Worse, you might even get discouraged and give up all your efforts.
The real problem is that there are a lot of things to take into account in a Data Science project, from data collection, to data preparation, to the choice of model, to the optimisation of the algorithm.
The solution to all this is a clear plan with simple to follow but very powerful instructions, applicable to any Machine Learning project.
That’s why I wanted to create a complete course, which details all the steps of Machine Learning projects, from start to finish, by implementing them directly in Python.
Be careful, this training is intense, many technical concepts are covered, as well as several Python libraries and functions. You need to be motivated.
You will have to carefully follow the different steps mentioned to make sure that the final result is valuable.
After completing this training, you will know how to solve a problem using Machine Learning and Python. You will discover how powerful this discipline can be.
Whenever you will be given any set of data, you will switch on your computer and start your project by following the different steps presented here. You will no longer be confused by where to start.
As you keep coding, you will remain confident in your approach because you will know where you are going.
You will have more and more ideas of how to apply it in your professional life.
In this course, you will discover the powerful technique of feature engineering.
You will learn 3 simple but powerful techniques used to explore data.
You will discover how to automate data preparation with 4 tools used by data scientists.
Finally, you will learn how to significantly improve your model, automatically, with a very robust method.
If you currently know few Machine Learning models, don’t worry, I explain the intuition behind the models I use. This course is also suitable for those who only have a few basics in Python because the code is explained as we go along.
This course is a real guide for any Python Learning Machine project.
See you in the training.
See you soon,
Damien
Course Curriculum
Chapter 1: Introduction to Machine Learning
Lecture 1: Presentation of the course
Lecture 2: Data Science vs Machine Learning
Lecture 3: The different steps of a Machine Learning project
Chapter 2: Prepare the workspace
Lecture 1: Downloading development software for Data Science
Lecture 2: Installing the required Python libraries
Lecture 3: Downloading the data
Chapter 3: Exploring the data
Lecture 1: Getting familiar with the IDE
Lecture 2: Loading the data in the IDE
Lecture 3: Manipulating the data in Python
Lecture 4: Feature Engineering in Data Science
Lecture 5: Interpreting the measures of the data
Lecture 6: Creating graphs for visualizations
Lecture 7: Studying the correlation between variables
Chapter 4: Preparing the data for the Machine Learning algorithms
Lecture 1: Studying the predicted variable
Lecture 2: Splitting the data between a training and a test set
Lecture 3: Cleaning the data with the pipelines
Chapter 5: Training your Machine Learning models
Lecture 1: Focus on the Linear Regression
Lecture 2: Training your first Machine Learning model
Lecture 3: Testing the performance of your Machine Learning model
Lecture 4: Focus on the Random Forest Regressor
Lecture 5: Training another Machine Learning model
Lecture 6: Improving the models with Grid Search
Chapter 6: Communicating the results
Lecture 1: Synthesizing the important results
Chapter 7: Conclusion of the course
Lecture 1: Summary of the different steps of a Machine Learning project
Lecture 2: Your feedback on the course
Instructors
-
Damien Chambon
Coaching en Data Science
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 2 votes
- 5 stars: 1 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!
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