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 expert.
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 Machine learning has more than 60 percent job for Data Science ,Machine learning and Deep learning job requirement.
Machine learning has add many new job in existing vertical like telecom,Finance ,Insurance ,Storage and Healthcare.
Minimum Qualification for this course:
Masters in Science ,Maths and Statistic or B.E/B.Tech or M.C.A
Machine learning course offline:
We have offline batch in Machine learning with Python near Manyatta Tech Park, Banaswadi and Kalyan Nagar proximity area.
|Introduction to machine learning and artificial intelligence|
|Machine learning fundamentals||00:00:00|
|Supervised learning algorithm||00:00:00|
|Unsupervised learning algorithm||00:00:00|
|Introduction to Exploratory Data Analysis|
|Introduction to Python programming ,method,and Python variable ,loop and statement|
|Machine learning fundamentals-Numpy,Pandas,Scipy,Sklearn and Matplotlib|
|Matplotlib and different example of data plotting like scatter plot,bar plot,box plot ,line graph etc|
|Supervised and Unsupervised learning algorithm|
|Linear regression with single and multiple variable- Basic Machine learning for Regression Problem||00:00:00|
|Logistic Regression with real time use case||00:00:00|
|K Nearest Neighbours -Machine learning||00:00:00|
|K means clustering -Machine learning||00:00:00|
|Naive Bayes Theorem -A machine learning approach||00:00:00|
|Dimension Reduction and Principal Component Analysis- Unsupervised Machine learning||00:00:00|
|Principle of PCA and Dimension Reduction||00:00:00|
|Apply PCA in large Features without impacting Data||00:00:00|
|Support Vector Machine and Dimension Reduction on Data Set||00:00:00|
|Decession Tree and Random Forest Algorithm -Machine learning with python|
|Work on Wine DataSet and Titanic Dataset||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|
|Introduction to ANN and DNN||00:00:00|
|Understanding activation function,Epoch,hyper parameter Tuning||00:00:00|
|Work on Employee Retention and Fraud Analytics Project with Neural Network|
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