This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

A Road map connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.

Below are few Applications of Machine Learning in Practical Real World

• Machine learning can help with the diagnosis of diseases. Many physicians use chat bot with speech recognition capabilities to discern patterns in symptoms. Real world examples for medical diagnosis: Assisting in formulating a diagnosis or recommending a treatment option.
  
  

• Google Maps uses machine learning in combination with various data sources including aggregate location data, historical traffic patterns, local government data, and real time feedback from users, to predict traffic.
  
  

Python leads the pack, with 57% of data scientists and machine learning developers using it and 33% Prioritising it for development. So, In this course also you will able learn Basics of Python to Advance State of the Art Techniques of  Deep Learning Models.

There are 4 different sections in this course for complete understanding of all the concepts in Artificial Intelligence such as Python, Machine Learning, Deep Learning, Time Series Analysis.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:

PYTHON  

Data Structures, List, Tuples, Dictionary, Libraries, Functions, Operators etc

Data Cleaning and Preprocessing

MACHINE LEARNING  

Regression: Simple Linear Regression, , SVR, Decision Tree , Random Forest,

Clustering: K Means, Hierarchical Clustering Algorithms

Classification: Logistic Regression, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

Natural Language Processing: Bag of words model and algorithms for NLP

DEEP LEARNING  

Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Long short term Memory, Vgg16 , Transfer learning, Web Based Flask Application.

Moreover, the course is packed with practical exercises that are based on real life examples. So not only will you learn the theory, but you will also get some hands on practice building your own models.