Natural Language Processing with Python
In this course, you’ll learn Natural Language Processing (NLP) basics, such as how to identify and separate words, how to extract topics in a text, and how to build your own fake news classifier. You’ll also learn how to use basic libraries such as NLTK, alongside libraries which utilize deep learning to solve common NLP problems. This course will give you the foundation to process and parse text as you move forward in your Python learning.
Machine Learning with R
Machine Learning with R training is a comprehensive course for mastering various aspects of machine learning. You will learn about machine learning with R programming, supervised and unsupervised learning, Support Vector Machines, Random Forest Classifiers, the best practices of machine learning and more through hands-on projects and case studies.
Machine Learning With Python
Machine Learning with Python course discusses concepts of the Python language such as file operations, sequences, object-oriented concepts, etc. along with some of the most commonly leveraged Python libraries like Numpy, Pandas, Matplotlib, etc. The course will then move on to introduce learners to the detailed mechanisms of Machine Learning. Learners will understand in detail the significance of the implementation of Machine Learning in the Python programming language, and leverage this knowledge in their role as data scientists.

Data science and machine learning are toppers in the technical world today. Machine learning brings computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques we can automate any machine learning analytical model.
you will work through various examples on advanced algorithms, and focus a bit more on some visualization options we will show the next example on letter recognition, where you will train a program to recognize letters using a support Vector machine, examine the results, and plot a confusion matrix. With the help of various projects you will find it intriguing to acquire the mechanics of several important machine learning algorithms.