Projects in Machine Learning : Beginner To Professional (Udemy.com)

A complete guide to master machine learning concepts and create real world ML solutions

( 96 Reviews )

Created by: Eduonix Learning Solutions

Produced in 2018

What you will learn

Learn core concepts of Machine Learning
Learn about differnt types of machine learning algorithms
Build real world projects using Supervised and Unsupervised learning algorithms
Learn to implement neural networks

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 80 / 100

Course Description

Update: This course has been updated to include 8 projects that will give you a real-world experience with different concepts of Machine Learning. Keep an eye out for more projects that will be added to this course in the future!
If you've ever wanted Jetsons to be real, well we aren't that far off from a future like that. If you've ever chatted with automated robots, then you've definitely interacted with machine learning. From self-driving cars to AI bots, machine learning is slowly spreading it's reach and making our devices smarter.
Artificial intelligence is the future of computers, where your devices will be able to decide what is right for you. Machine learning is the core for having a futuristic reality where robot maids and robodogs exist. Machine learning includes the algorithms that allow the computers to think and respond, as well as manipulate the data depending on the scenario that's placed before them.
So, if you've ever wanted to play a role in the future of technology development, then here's your chance to get started with Machine Learning. Because machine learning is complex and tough, we've designed a course to help break it down into more simple concepts that are easier to understand.
This course covers the basic concepts of machine learning that are crucial to get started on the journey of becoming a developer for machine learning. This course covers all the different algorithms that are required to simulate the right environment for your computer.
The course will start at the very beginning and delve right into machine learning, before breaking down the most important concepts principles. However, the course does require you to have a mathematical background as machine learning relies heavily on mathematical concepts. It also requires you to have some experience with Python principles which will be required when we put the algorithms to test in actual real-world Python projects.
The course covers a number of different machine learning algorithms such as supervised learning, unsupervised learning, reinforced learning and even neural networks. From there you will learn how to incorporate these algorithms into actual projects so you can see how they work in action! But, that's not all. In addition to quizzes that you'll find at the end of each section, the course also includes a 6 brand new projects that can help you experience the power of Machine Learning using real-world examples!
9 Projects That Are Included in This Course:

Project 1 -Board Game Review Prediction In this project, you'll see how to perform a linear regression analysis by predicting the average reviews on a board game in this project.
Project 2 Credit Card Fraud Detection In this project, you'll learn to focus on anomaly detection by using probability densities to detect credit card fraud.
Project 3 Getting Started with Natural Language Processing In Python This project will focus on Natural Language Processing (NLP) methodology, such as tokenizing words and sentences, part of speech identification and tagging, and phrase chunking.

Project 4 Obtaining Near State-of-the-Art Performance on Object Recognition Tasks Using Deep Learning In this project, will use the CIFAR-10 object recognition dataset as a benchmark toimplement a recently published deep neural network.

Project 5 Image Super Resolution with the SRCNN Learn how to implement and use a Tensorflow version of the Super Resolution Convolutional Neural Network (SRCNN) for improving image quality.
Project 6 Natural Language Processing: Text Classification In this project, you'll learn an advanced approach to Natural Language
Processing by solving a text classification task using multiple classification algorithms.
Project 7 K-Means Clustering For Image Analysis In this project, you'll learn how to use K-Means clustering in an unsupervised
learning method to analyze and classify 28 x 28 pixel images from the MNIST dataset.
Project 8 Data Compression & Visualization Using Principle Component Analysis This project will show you how to compress
our Iris dataset into a 2D feature set and how to visualize it through a normal x-y plot using k-means clustering.

All of this and so much more is included in this course. So, what are you waiting for?
Get started in machine learning with this epic course that makes machine learning simpler and easy to understand! Enroll now to step into the future of programming.

Who this course is for:

Students who will like to understand and use Machine learning in real world projects will find this course very useful

Time: 15.5h

Instructor Details

Eduonix Learning Solutions

4.0 Rating
96 Reviews

Eduonix creates and distributes high quality technology training content. Our team of industry professionals have been training manpower for more than a decade. We aim to teach technology the way it is used in industry and professional world. We have professional team of trainers for technologies ranging from Mobility, Web to Enterprise and Database and Server Administration.Hi there,
I'm in charge of Course Development at Eduonix Learning Solutions.
I'm here to make sure that all of Eduonix' courses are the best possible, and that they help you improve your skills!
If you feel like any of our courses could be improved, let me know and we'll update them accordingly.
You can be sure that all our future courses will be top-quality and constantly updated with new content!
See you soon,
Samy

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Reviews

4.0

96 total reviews

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Write a Review

By Tarun Goyal

I have just started this course but one thing I hated is the audio quality of tutorials of Section 1.

By Sunmeen oberoi

Great experience

By Dharmesh Dev

Theory was little boring, the author could have made it more interesting to listening, but 5 star for projects.

By Twaine Twaine

I have never had any experience before with machine learning and AI its incredible the way this instructor lays it out. with some body that did not even finish the 9th grade and dropped out of high school. the way this instructor explains this technology is better than any schooling I have ever had. man he is good I really under stand this and I am applying to my trading I am FX trader for the last 15 years and the last five years I have been working on testing my own strategy and now am ready tp take it to the next level and be able input it into machine learning and AI algorithms to make it even better and that's going to be hard to do because its exceptional know. and man this course is allowing me to under stand the critical thinking elements and comparisons and the architecture of machine learning and AI that I need to build this bot. so thank you very much. Twaine

By Yash Trivedi

It provides good theoretical knowledge with examples but hoped it to be more detailed.

By Neelakantha

The best one! Keep it up!

By Johan Snels

Great course if you want to become familiar with Machine Learning. Clear examples and well structured.

By Augustin Milandu

very good course & the instructor is fantastic.

By Senn Lee

The more I listen, the better I understand. Great news.

By Somenath Chowdhury

Choose Algorithm video is good, where proper explanation with diagram are present.

By Krishna Kumar Mahto

The openAI gym intro is confusing. The instructure doesn't explain what each line in the code does.

I had to look up to the openAI gym to know what gym.make() does, env.render()..etc.

It might appear obvious to some, but an abstract idea about what the particular method/function does, would have made it less hard.

By Benya Adeyanju Jamiu