Machine learning certification course in Bangalore

Sniffer Search provide best Machine learning certification course in Bangalore. This is a instructor lead program from machine learning scholars and designed by professor from TOP Universities


At the end of the course you will learn :

  • Data Science using Python
  • Statistical Analysis
  • Supervised and Unsupervised learning algorithm and implementation using Python
  • Reinforcement learning algorithm using Python code imlementation
  • Neural network  using Google TensorFlow and Keras Framework

Why Sniffer Search:

The  Machine Learning certification using Python  is designed and customized as per industry needs.This is a job oriented course where  all qualified candidate are source for interview along with resume preparation.

Why Machine Learning with Python:

Machine Learning using Python  is most popular now because of Python popularity,easy to learn and available Data Science package(Numpy,scipy,pandas,Scikit-learn) and compatibility with google tensorflow and keras framework for Deep learning.

Python for Data Science has more than 60 percent job for Data Science ,Machine learning and Deep learning  job requirement.


Minimum Qualification for this course:

Masters in Science ,Maths and Statistic or B.E/B.Tech  or M.C.A




Course Curriculum

Introduction to machine learning and artificial intelligence
Machine learning fundamentals 00:00:00
Evolution of artificial Intelligence 00:00:00
Introduction to Exploratory Data Analysis
The process of a Data Analytics for supervised and Unsupervised learning
Introduction to Python programming ,method,and Python variable ,loop and statement
python data structure -Numpy,Scipy and Pandas
Matplotlib and different example of data plotting like scatter plot,bar plot,box plot ,line graph etc
Supervised and Unsupervised learning algorithm
Linear regression for single and multiple variable 00:00:00
Logistic Regression with real time use case 00:00:00
K Nearest Neighbours 00:00:00
K means clustering 00:00:00
Naive Bayes Theorem 00:00:00
Dimension Reduction and Principal Component Analysis 00:00:00
Support Vector Machine and Dimension Reduction on Data Set 00:00:00
Gradient Boosting to increase performance of machine learning algorithm 00:00:00
Reinforcement learning with use case and sample code
Neural Network - how to create artificial Intelligence using Neural network
How to recognize image using neural network- real time example
How to work with large dataset - a comparison study of different algorithm and rule of thumb to follow while choosing algorithm to find prediction or finding hidden pattern

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