From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase

Here stands an exclusive chance for you to get acquainted and learn everything about Machine Learning, NLP & Python with this highly affordable course by a team of highly qualified & experienced instructors.

This course will provide you with all the practical as well as theoretical knowledge related to Machine Learning, NLP & Python. Also, it’ll help you in understanding the related complexities. Each and every concept in this course has been visually described and elaborated,  in order to make it easy for you to understand and learn.

This course has 93 videos in total and will take you through all of these in maximum 20 hours. You can watch the videos at your own pace and accordingly can raise doubts or questions if you get stuck. For enrollment in this course all you need is understanding of undergraduate level mathematics, a bit of Python related knowledge would also be quite helpful.

This course has provided you with the source code and will teach you the undermentioned concepts:

• K-nearest Neighbours
• Supervector Machines
• Artificial Neural Networks
• K-means
• Hierarchical Clustering
• Principle Component Analysis

Natural Language Processing with Python: 

• Corpora,
• Stop-words,
• sentence and word parsing,
• auto-summarization,
• sentiment analysis (as a special case of classification),
• TF-IDF, Document Distance,

Sentiment Analysis: 

• Approaches to solving – Rule-Based ,
• ML-Based ,
• Training ,
• Feature Extraction,
• Sentiment Lexicons,
• Regular Expressions,
• Twitter API,
• Sentiment Analysis of Tweets with Python

Mitigating Over-fitting with Ensemble Learning:

• Decision tree learning,
• Over-fitting in decision trees,
• Techniques to mitigate over-fitting (cross validation, regularization),
• Ensemble learning and Random forests

Some exceptional benefits associated with this course enrollment are:

• Quality course material
• Instant & free course updates
• Access to all Questions & Answers initiated by other students as well
• Personalized support from the instructor’s end on any issue related to the course
• Few free lectures for a quick overview