1.
Kachhua.com​ ​Machine
Learning Python Course
​ Learn Anwhere, Any time
● Kachhua is India's No.1 Online Education Marketplace
● Online Courses, Books, Stationary, Projects and much more
● Machine Learning Python Language : most of the techniques are
explained with the help of animations to help you understand
better.
● URL :
https://kachhua.com/items/machine-learning-nlp-python-cut-to-the-chase-from-0-to-1
●

2.
What is machine learning python course ?
➢ Prerequisites: No prerequisites, knowledge of some undergraduate
level mathematics would help but is not mandatory. Working
knowledge of Python would be helpful if you want to run the source
code that is provided.
➢ This course is a down-to-earth, shy but confident take on machine
learning techniques that you can put to work today
➢ The course is down-to-earth : it makes everything as simple as
possible - but not simpler
Who should buy this course?
➢ No prerequisites, knowledge of some undergraduate level
mathematics would help but is not mandatory. Working knowledge of
Python would be helpful if you want to run the source code that is
provided.
➢ Analytics professionals, modelers, big data professionals who haven't
had exposure to machine learning
➢ Engineers who want to understand or learn machine learning and
apply it to problems they are solving
➢ Product managers who want to have intelligent conversations with
data scientists and engineers about machine learning
➢ Tech executives and investors who are interested in big data,
machine learning or natural language processing
➢ MBA graduates or business professionals who are looking to move to
a heavily quantitative role

3.
Want to learn Python Machine Learning, NLTK? Check Machine Learning Course by
Loonycorn. Beginner to Expert level course. High School Maths will be helpful but not
mandatory. Course covering Machine Learning, Natural Language Processing with Python,
Sentiment Analysis total 82 lectures, total length 20.5 hours. buy now from Kachhu.com
Which topics are covered in machine learning python
for Beginners :
Section 1: Introduction
Section 2: Jump right in : Machine learning for Spam detection
Section 3: Naive Bayes Classifier
Section 4: K-Nearest Neighbors
Section 5: Support Vector Machines
Section 6: Clustering as a form of Unsupervised learning
Section 7: Association Detection
Section 8: Dimensionality Reduction
Section 9: Artificial Neural Networks
Section 10: Regression as a form of supervised learning
Section 11: Natural Language Processing and Python
Section 12: Sentiment Analysis
Section 13: Decision Trees
Section 14: A Few Useful Things to Know About Overfitting
Section 15: Random Forests
Section 16: Recommendation Systems
Section 17: Recommendation Systems in Python
Section 18: A Taste of Deep Learning and Computer Vision