The Complete Machine Learning Course with Python

4.3 (2458)
MOOC
The Complete Machine Learning Course with Python
Payment
Learning paid
Language
English
Duration
17.5 hours course
Course by Udemy
$ 129.99
The Complete Machine Learning Course with Python
$ 129.99
What will you learn?
Machine Learning Engineers earn on average $166,000 - become an ideal candidate with this course!
Solve any problem in your business, job or personal life with powerful Machine Learning models
Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells & more
Go from zero to hero in Python, Seaborn, Matplotlib, Scikit-Learn, SVM, unsupervised Machine Learning etc
About the course

The Complete Machine Learning Course in Python has been FULLY UPDATED for November 2019!

With brand new sections as well as updated and improved content, you get everything you need to master Machine Learning in one course! The machine learning field is constantly evolving, and we want to make sure students have the most up-to-date information and practices available to them:

Brand new sections include:

  • Foundations of Deep Learning covering topics such as the difference between classical programming and machine learning, differentiate between machine and deep learning, the building blocks of neural networks, descriptions of tensor and tensor operations, categories of machine learning and advanced concepts such as over- and underfitting, regularization, dropout, validation and testing and much more.
  • Computer Vision in the form of Convolutional Neural Networks covering building the layers, understanding filters / kernels, to advanced topics such as transfer learning, and feature extractions.

And the following sections have all been improved and added to:

  • All the codes have been updated to work with Python 3.6 and 3.7
  • The codes have been refactored to work with Google Colab
  • Deep Learning and NLP
  • Binary and multi-class classifications with deep learning

Get the most up to date machine learning information possible, and get it in a single course! 

                                                                *         *         *

The average salary of a Machine Learning Engineer in the US is $166,000! By the end of this course, you will have a Portfolio of 12 Machine Learning projects that will help you land your dream job or enable you to solve real life problems in your business, job or personal life with Machine Learning algorithms.

Come learn Machine Learning with Python this exciting course with Anthony NG, a Senior Lecturer in Singapore who has followed Rob Percival’s “project based" teaching style to bring you this hands-on course.

With over 18 hours of content and more than fifty 5 star ratings, it's already the longest and best rated Machine Learning course on Udemy!

Build Powerful Machine Learning Models to Solve Any Problem

You'll go from beginner to extremely high-level and your instructor will build each algorithm with you step by step on screen.

By the end of the course, you will have trained machine learning algorithms to classify flowers, predict house price, identify handwritings or digits, identify staff that is most likely to leave prematurely, detect cancer cells and much more!

Inside the course, you'll learn how to:

  • Gain complete machine learning tool sets to tackle most real world problems
  • Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them.
  • Combine multiple models with by bagging, boosting or stacking
  • Make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data
  • Develop in Jupyter (IPython) notebook, Spyder and various IDE
  • Communicate visually and effectively with Matplotlib and Seaborn
  • Engineer new features to improve algorithm predictions
  • Make use of train/test, K-fold and Stratified K-fold cross validation to select correct model and predict model perform with unseen data
  • Use SVM for handwriting recognition, and classification problems in general
  • Use decision trees to predict staff attrition
  • Apply the association rule to retail shopping datasets
  • And much much more!

No Machine Learning required. Although having some basic Python experience would be helpful, no prior Python knowledge is necessary as all the codes will be provided and the instructor will be going through them line-by-line and you get friendly support in the Q&A area. 

Make This Investment in Yourself

If you want to ride the machine learning wave and enjoy the salaries that data scientists make, then this is the course for you!

Take this course and become a machine learning engineer!

Program
Introduction
What Does the Course Cover?
How to Succeed in This Course
Project Files
Getting Started with Anaconda
[Windows OS] Downloading & Installing Anaconda
The instructions provided are for installation of Anaconda on a Windows OS.https://conda.io/docs/user-guide/install/windows.html

For instruction on how to install Anaconda on a Mac OS, follow this linkhttps://conda.io/docs/user-guide/install/index.html#regular-installation
andhttps://conda.io/docs/user-guide/install/macos.html

[Windows OS] Managing Environment
[Mac OS] Intructions on Installing Anaconda and Managing Environment
Practice Activity: Create a New Environment
In this practice activity / quiz, please:
  • Create a new virtual environment
  • Calling it "irisproject"
  • Ensure that Anaconda, Jupyter Notebook, andSpyder has been successfully installed
Do make sure you have successfully completed the above before you proceed to the next portion. We will need it for the next lecture.
Navigating the Spyder & Jupyter Notebook Interface
Downloading the IRIS Datasets
Data Exploration and Analysis
Requirements
  • Basic Python programming knowledge is necessary
  • Good understanding of linear algebra
Lecturers
Codestars by Rob Percival
Codestars by Rob Percival
Teaching the Next Generation of Coders
Anthony NG
Anthony NG
Algorithmic Trading Workshop Researcher and Conductor
Rob Percival
Rob Percival
Web Developer And Teacher
Platform
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Udemy courses are suited to professional development. The platform is organized in such a way that it is experts themselves that decide the topic and when the course will start. All supporting documents are made available to you for lifetime access. On this platform, you can find a course on about any subject, and that is no exaggeration – from a tutorial on how to ride a motorcycle, to managing the financial markets. The language and the course format are established by the teacher. This is why it is important to read the information about the course carefully before parting with any money.
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