Have you ever wondered how self-driving cars are running on roads or how Netflix recommends the movies which you may like or how Amazon recommends you products or how Google search gives you such an accurate results or how speech recognition in your smartphone works or how the world champion was beaten at the game of Go?
Machine learning is behind these innovations. In the recent times, it has been proven that machine learning and deep learning approach to solving a problem gives far better accuracy than other approaches. This has led to a Tsunami in the area of Machine Learning.
Most of the domains that were considered specializations are now being merged into Machine Learning. This has happened because of the following:
Better research and algorithms
Better computing resources
Distributed computing infrastructures
Availablity of Big Data
Every domain of computing such as data analysis, software engineering, and artificial intelligence is going to be impacted by Machine Learning. Therefore, every engineer, researcher, manager or scientist would be expected to know Machine Learning.
So naturally, you are excited about Machine learning and would love to dive into it. This specialization is designed for those who want to gain hands-on experience in solving real-life problems using machine learning and deep learning. After finishing this specialization, you will find creative ways to apply your learnings to your work.
For example
You would like to build a robot which can recognize faces or change the path after discovering obstacles on the path.
Or maybe you would like to unearth hidden gems (like predicting next year revenue or fraudulent transactions or building a recommendation engine etc) in your company's tons of data(logs, financial records, HR reports or e-commerce transactions reports).
See you in the specialization and happy learning!
Program Highlights
Certificate of Completion by CloudxLab
Work on about 18+ projects to get hands-on experience
CloudxLab is a team of developers, engineers, and educators passionate about building innovative products to make learning fun, engaging, and for life. We are a highly motivated team who build fresh and lasting learning experiences for our users. Powered by our innovation processes, we provide a gamified environment where learning is fun and constructive. From creative design to intuitive apps we create a seamless learning experience for our users. We upskill engineers in deep tech - make them employable and future-ready.
9.5 Evaluating Actions: The Credit Assignment Problem
9.6 Policy Gradients
9.7 Markov Decision Processes
9.8 Temporal Difference Learning and Q-Learning
9.9 Deep Q-Learning Variants
9.10 The TF-Agents Library
Projects
Project 1. Analyze Emails
We will churn the mail activity from various individuals in an open source project development team.
Project 2. Predict bikes rental demand
We will build a model to predict the bikes demand given the past data.
Project 3. Noise removal from the images
We will Build a model that takes a noisy image as an input and outputs the clean image.
Project 4. Predict which passengers survived in the Titanic shipwreck
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. In this project, you build a model to predict which passengers survived the tragedy.
Project 5. Build a spam classifier
We will learn how to build a model to classify email as spam or ham. First, download examples of spam and ham from Apache SpamAssassin’s public datasets and then train a model to classify email.
Project 6. Build an Image Classifier in Fashion MNIST dataset
We will see how to classify images from the Fashion MNIST dataset using scikit-learn, and Python.
Project 7. Deploy Machine Learning models to Production using Flask
We will learn how to deploy a machine learning model as a web application using the Flask framework.
Project 8. Build an Image Classifier in Fashion MNIST dataset
Classify images from the Fashion MNIST dataset using Tensorflow 2, Matplotlib, and Python.
Project 9. Training from Scratch vs Transfer Learning
Learn how to train a neural network from scratch to classify data using TensorFlow 2, and how to use the weights of an already trained model to achieve classification to another set of data.
Project 10. Working with Custom Loss Function
Create a custom loss function in Keras with TensorFlow 2 backend.
Project 11. Image Classification with Pre-trained Keras models
Learn how to access the pre-trained models(here we get pre-trained ResNet model) from Keras of TensorFlow 2 to classify images.
Project 12. Build cats classifier using transfer learning
In this project, you will build a basic neural network to classify if a given image is of cat or not using transfer learning technique with Python and Keras.
Project 13. Mask R-CNN with OpenCV for Object Detection
Learn how to read a pre-trained TensorFlow model for object detection using OpenCV.
Project 14. Art Generation Project
Use TensorFlow 2 to generate an image that is an artistic blend of a content image and style image using Neural Style Transfer.
Project 15. NYSE Stock Closing Price Prediction using TensorFlow 2 and Keras
Predict stock market closing prices for a firm using GRU, a state-of-art deep learning algorithm for sequential data, with Keras and Python.
Project 16. Sentiment Analysis using IMDB dataset
Create a sentiment analysis model with the IMDB dataset using TensorFlow 2.
Project 17. Autoencoders for Fashion MNIST
Learn how to practically implement the autoencoder, stacking an encoder and decoder using TensorFlow 2, and depict reconstructed output images by the autoencoder model using the Fashion MNIST dataset.
Project 18. Deploy Image Classification Pre-trained Keras model using Flask
Learn how to deploy a deep learning model as a web application using the Flask framework.
Apply Now
Prerequisites
This course is for engineers, product managers and anyone who wants to learn. We will cover foundations of linear algebra, calculus and statistical inference where ever required so that you can learn the concepts effectively. There is no prerequisite or programming knowledge required.
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Machine Learning Specialization (Includes Deep Learning) (lifetime course access) + 90 days Cloud Lab
“Sessions were great, pace was also very good. Each of the steps were explained well multiple times to ensure everyone understands the concepts. Thanks Sandeep!”
Nitin Nigam
“Thanks a lot,it was great course! I'm happy that you lead in this path to AI/ML/DL.I hope to continue to collaborate with you in future.”
Domenico Flioravanti
“Thank you so much Sandeep for all your great sessions. It will help in our career a lot. Your session is very much explanatory and understandable. Kudos to you.Thanks for all your hard work and time. Definitely, we will recommend all our friends and colleagues to attend your different course.Thanks a ton”
Hemanta Lenka
“I have been using CloudxLab for a while now, and they are amazing! The best part about using CloudxLab is that you do not need to wait for someone to tell you whether what you did was right or not, it is done automatically on the go. The training materials are of top notch quality. If you get stuck, they have a huge community of trainers and learners to help you out with all your doubts. They have a course structure for everyone, whether you are new to programming or are a seasoned programmer, they have something to offer you. And they are affordable too! I would recommend CloudxLab all the time.”
Rajtilak Bhattacharjee
“This course is suitable for everyone. Me being a product manager had not done hands-on coding since quite some time. Python was completely new to me. However, Sandeep Giri gave us a crash course to Python and then introduced us to Machine Learning. Also, the CloudxLab’s environment was very useful to just log in and start practising coding and playing with things learnt. A good mix of theory and practical exercises and specifically the sequence of starting straight away with a project and then going deeper was a very good way of teaching. I would recommend this course to all.”
Kamal Upadhyay
“It has been a wonderful learning experience with CXL. This is one of the courses that will probably stay with me for a significant amount of time. The platform provides a unique opportunity to try hands-on simultaneously with the coursework in an almost real-life coding example. Besides, learning to use algebra, tech system and Git is a good refresher for anyone planning to start or stay in technology. The course covers the depth and breadth of ML topics. I specifically like the MNIST example and the depth to which it goes in explaining each and every line of code. Would definitely recommend the instructor-led course.”
Pratik Sonthalia
“This is one of the best-designed course, very informative and well paced. The killer feature of machine/deep learning coursed from CloudxLab is the live session with access to labs for hands-on practices! With that, it becomes easy following any discourse, even if one misses the live sessions(Read that as me!). Sandeep(course instructor) has loads of patience and his way of explaining things are just remarkable. I might have better comments to add here, once I learn more! Great Jobs guys!”
Dhyan Prem
Senior Software Developer at Decision Resources Group
If you are unhappy with the product for any reason, let us know within 7 days of purchasing or upgrading your account, and we'll cancel your account and issue a full refund. Please contact us at reachus@cloudxlab.com to request a refund within the stipulated time. We will be sorry to see you go though!
This course is for engineers, product managers and anyone who wants to learn. We will cover foundations of linear algebra, calculus and statistical inference where ever required so that you can learn the concepts effectively. There is no prerequisite or programming knowledge required.
We understand that you might need course material for a longer duration to make most out of your subscription. You will get lifetime access to the course material so that you can refer to the course material anytime.
