Learn Python, NumPy, Pandas, scikit-learn, Regression, Clustering, Classification, SVM, Random Forests, Decision Trees, Dimensionality Reduction, TensorFlow 2, Keras, Convolutional & Recurrent Neural Networks, Autoencoders, Reinforcement Learning From Industry Experts
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:
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
See you in the specialization and happy learning!
Churn the mail activity from various individuals in an open source project development team.
Build a model to predict the bikes demand given the past data.
Build a model that takes a noisy image as an input and outputs the clean image.
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.
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.
Classify images from the Fashion MNIST dataset using scikit-learn, and Python.
Learn how to deploy a machine learning model as a web application using the Flask framework.
Classify images from the Fashion MNIST dataset using Tensorflow 2, Matplotlib, and Python.
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.
Create a custom loss function in Keras with TensorFlow 2 backend.
Learn how to access the pre-trained models(here we get pre-trained ResNet model) from Keras of TensorFlow 2 to classify images.
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.
Learn how to read a pre-trained TensorFlow model for object detection using OpenCV.
Use TensorFlow 2 to generate an image that is an artistic blend of a content image and style image using Neural Style Transfer.
Predict stock market closing prices for a firm using GRU, a state-of-art deep learning algorithm for sequential data, with Keras and Python.
Create a sentiment analysis model with the IMDB dataset using TensorFlow 2.
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.
Learn how to deploy a deep learning model as a web application using the Flask framework.
Our course is exhaustive and the certificate rewarded by us is proof that you have taken a big leap in Machine Learning and Deep Learning.
The knowledge you have gained from working on projects, videos, quizzes, hands-on assessments and case studies gives you a competitive edge.
Highlight your new skills on your resume, LinkedIn, Facebook and Twitter. Tell your friends and colleagues about it.
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!
No, we will provide you with the access to our online lab and BootML so that you do not have to install anything on your local machine
Please log in at CloudxLab.com with your Gmail Id and access your course under "My Courses".
We have created a set of Guided Projects on our platform. You may complete these guided projects and earn the certificate for free. Check it out here
Have more questions? Please contact us at reachus@cloudxlab.com
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.
Machine learning courses in especially the Artificial Intelligence for the manager course is excellent in CloudxLab. I have attended some of the course and able to understand as Sandeep Giri sir has taught AI course from scratch and related to our data to day life…
He even takes free sessions to helps students and provides career guidance.
His courses are worthy and even just by watching YouTube video anyone can easily crack the AI interview.
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!
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.
I took both the machine learning and deep learning course at CloudXLab. I came into the first part of the course with some knowledge of machine learning but the class really helped me understand some of the topics a lot clearer. I think the best part of the class is the instructor Sandeep. He is very knowledgeable and does a really good job explaining topics that can be nebulous at times. Another favorite part of the course are the online labs. I would watch the 3hr lecture the next day, and then work on the labs. The labs reinforces the lectures with questions and coding assignments. There is also a message board and a slack channel. I preferred using slack, but I think you get a quicker response if you use the message board. As far as the deep learning portion of the course, it was all new to me but I was building CNN and RNN models using TensorFlow after each 3hr lecture. Overall, I was very pleased with the course. I am hoping that CloudxLab will put together an advanced class focusing more on deploying models to the clouds, working with pipelines, DevOps etc…
I found the ML&DL course very well structured with ample examples and hands on exercises. Sandeep was very patient in answering questions and he made the training sessions very interactive. I would recommend this training to all who plan to take a dive into the world of machine and deep learning.
I have thoroughly enjoyed both the ML and DL courses from CloudXLab and will look forward to reviewing the videos/material at a later time. I’ve been to many meetups and paid sessions on ML /DL and this course beats most of them on the depth of topics and certainly breadth of topics. I’ve not taken any online courses (Andrew Ng, for example) to their conclusion, so I won’t draw a conclusion there. For an instructor-led, interactive course, I would expect to pay many times more for a class (ML and DL) such as this in the US. The instructor is easy to understand, has extensive experience, and truly cares about the student knowing the material.
A very well structured instructor-led course. The instructor was very thorough, and always willing to answer questions and clarify coursework, no matter how minor. The course described the theory of machine/deep learning well, but also followed through with very thorough examples to demonstrate the practical implementations of the theory. This leads nicely into the student exercises, which served to solidify the instructor's teachings and encourage experimentation. The resources provided for students was exceptional and presented in a very user-friendly format.
My only complaint is that the course went quite overtime, but I also appreciate Sandeeps dedication to quality and ensuring that he finished teaching us everything adequately.
I have been using CloudxLab for Machine Learning and based on experience I can say that they have done a fabulous job in training and certification process which makes the user so interactive with faculty and software intuitive.