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Development Data Science Machine Learning

Projects in Machine Learning : Beginner To Professional

A complete guide to master machine learning concepts and create real world ML solutions
Rating: 4.0 out of 54.0 (538 ratings)
4,601 students
Created by Eduonix Learning Solutions, Eduonix-Tech ., Samy Eduonix
Last updated 12/2018
English
English [Auto]
30-Day Money-Back Guarantee

What you'll 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

Course content

14 sections • 66 lectures • 15h 27m total length

  • Preview00:58
  • Preview10:53
  • Types and Applications of ML
    25:45
  • Preview09:43
  • Essential Math for ML and AI
    17:04
  • Preview00:02
  • Preview00:02

  • Preview13:38
  • Preview16:35
  • Linear Methods for Regression
    11:51
  • Support Vector Machines
    15:42
  • Basis Expansions
    11:00
  • Model Selection Procedures
    13:58
  • Bonus! Supervised Learning Project in Python Part 1
    15:24
  • Bonus! Supervised Learning Project in Python Part 2
    15:23
  • Preview00:02
  • Preview00:02

  • Preview11:36
  • Preview14:13
  • Cluster Analysis
    13:19
  • Reinforcement Learning
    16:33
  • Bonus! KMeans Clustering Project
    14:14
  • Preview00:02
  • Preview00:02

  • Introduction to Neural Networks
    12:26
  • The Perceptron
    10:20
  • The Backpropagation Algorithm
    12:19
  • Training Procedures
    13:37
  • Convolutional Neural Networks
    15:55

  • Introduction to Real World ML
    10:34
  • Choosing an Algorithm
    08:44
  • Design and Analysis of ML Experiments
    10:22
  • Common Software for ML
    10:46
  • Preview00:02
  • Preview00:02

  • Setting up OpenAI Gym
    12:43
  • Building and Training the Network Part 1
    16:14
  • Building and Training the Network Part 2
    21:54

  • Intro
    01:39
  • Board Game Review Prediction - Building the Dataset Part 1
    09:49
  • Board Game Review Prediction - Building the Dataset Part 2
    16:41
  • Board Game Review Prediction - Training the Models
    15:17

  • Intro
    02:13
  • Credit Card Fraud Detection - The Dataset
    22:23
  • Credit Card Fraud Detection - The Algorithms
    20:41

  • Intro
    01:27
  • Tokenizing, Stop Words, and Stemming
    22:49
  • Tagging, Chunking, and Named Entity Recognition
    31:55
  • Text Classification
    23:57

  • Intro
    01:20
  • Loading and Preprocessing the CIFAR10 Dataset
    25:57
  • Building and Deploying the All-CNN Network Part 1
    25:24
  • Building and Deploying the All-CNN Network Part 2
    20:41

Requirements

  • Basic knolwedge of Python is required to compile and run the examples
  • Basic knolwedge of mathematics is assumed

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 to implement 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

Instructors

Eduonix Learning Solutions
1+ Million Students Worldwide | 200+ Courses
Eduonix Learning Solutions
  • 3.9 Instructor Rating
  • 87,980 Reviews
  • 1,218,536 Students
  • 244 Courses

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.

Eduonix-Tech .
E.
  • 3.9 Instructor Rating
  • 71,191 Reviews
  • 1,194,668 Students
  • 184 Courses
Samy Eduonix
Samy Eduonix
  • 4.1 Instructor Rating
  • 8,451 Reviews
  • 123,784 Students
  • 21 Courses

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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