ridhigrg

...

Full Bio 
Follow on

Today's Technology-Data Science
291 days ago

How to build effective machine learning models?
291 days ago

Why Robotic Process Automation Is Good For Your Business?
291 days ago

IoT-Advantages, Disadvantages, and Future
292 days ago

Look Artificial Intelligence from a career perspective
292 days ago

Every Programmer should strive for reading these 5 books
579849 views

Why you should not become a Programmer or not learn Programming Language?
239745 views

See the Salaries if you are willing to get a Job in Programming Languages without a degree?
152298 views

Have a look of some Top Programming Languages used in PubG
143877 views

Highest Paid Programming Languages With Highest Market Demand
137427 views

Machine Learning Python Deep Learning Sci-kit-Learn Algorithms Engineer NLP Code Datasets Data Scientist Data

An online diploma course in Machine Learning can make your career worth

By ridhigrg |Email | Nov 18, 2019 | 5646 Views

The Complete Machine Learning Course with Python
Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!

What you'll 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.

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 extraction.

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 prices, 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:
  • Set up a Python development environment correctly
  • Gain complete machine learning toolsets 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, precision, 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 the 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

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!

Who this course is for:
  • Anyone willing and interested to learn machine learning algorithm with Python
  • Anyone who has a deep interest in the practical application of machine learning to real-world problems
  • Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms
  • Any intermediate to advanced EXCEL users who are unable to work with large datasets
  • Anyone interested to present their findings in a professional and convincing manner
  • Anyone who wishes to start or transit into a career as a data scientist
  • Anyone who wants to apply machine learning to their domain

Source: HOB
Previous Story Next Story