Machine Learning and Deep Learning with JavaScript
Learn Machine Learning and Deep Learning from scratch using JavaScript and Tensorflow.js with hands-on projects
Ratings 2.73 / 5.00
What You Will Learn!
- Get acquainted with machine learning and deep learning capabilities using JavaScript and understand the JavaScript Machine Learning ecosystem
- Learn JavaScript libraries to build neural network models
- Know how to decide, analyze, and make predictions from real-world data
- Solve real-world problems such as predicting mental health issues
- Use clustering algorithms to understand customer behavior and categorize customers
- Train your machine learning models to work with different kinds of data
- Work with powerful algorithms using the pre-written libraries in Python
- Build deep learning models with TensorFlow .js and practice on realistic datasets
Description
Machine learning and Deep Learning have been gaining immense traction lately, but until now JavaScript developers have not been able to take advantage of it due to the steep learning curve involved in learning a new language. Here comes a browser based JavaScript library, TensorFlow.js to your rescue using which you can train and deploy machine learning models entirely in the browser. If you’re a JavaScript developer who wants to enter the field ML and DL using TensorFlow.js, then this course is for you.
This course takes a step by step approach to teach you how to use JavaScript library, TensorFlow.js for performing machine learning and deep learning on a day-to-day basis. Beginning with an introduction to machine learning, you will learn how to create machine learning models, neural networks, and deep learning models with practical projects. You will then learn how to include a pre-trained model into your own web application to detect human emotions based on pictures and voices. You will also learn how to modify a pre-trained model to train the emotional detector from scratch using your own data.
Towards the end of this course, you will be able to implement Machine Learning and Deep Learning for your own projects using JavaScript and the TensorFlow.js library.
Meet Your Expert(s):
We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:
Arish Ali started his machine learning journey 5 years ago by winning an all-India machine learning competition conducted by IISC and Microsoft. He was a data scientist at Mu Sigma, one of the biggest analytics firms in India. He has worked on some cutting-edge problems involved in multi-touch attribution modeling, market mix modeling, and Deep Neural Networks. He has also been an Adjunct faculty for Predictive Business Analytics at the Bridge School of Management, which along with Northwestern University (SPS) offers a course in Predictive Business Analytics. He has also worked at a mental health startup called Bemo as an AI developer where his role was to help automate the therapy provided to users and make it more personalized. He is currently the CEO at Neurofy Pvt Ltd, a people analytics startup.
Jakub Konczyk has done programming professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share them with others. He first discovered Machine Learning when he was trying to predict real estate prices in one of the early stages startups he was involved in. He failed miserably. Then he discovered a much more practical way to learn Machine Learning that he would like to share with you in this course. It boils down to Keep it simple!
Who Should Attend!
- This course is for JavaScript developers interested in Machine Learning and Deep learning. This course is also for data analysts and data scientists who want to explore the possibilities of Machine Learning and Deep Learning using JavaScript.
