Machine Learning Courses in Pune

Machine Learning Courses in Pune

Courses Info

EMAIL MARKETING COURSESHighlights of Python Machine Learning Training

This course will take you from zero to Python & Machine Learning hero in 45 days.
Learn Python from scratch and apply it to real Machine Learning problems.
Training Spread over 6 weekends to give you all required time for exercises and theory.
Training delivered in a “Live Online” session by a very experienced trainer from the United States.
After every weekend get a comprehensive assignment to further solidify your learning.
Lifetime access to recorded training session videos, so learning stays with you.
In-depth learning and practicals of Supervised & Unsupervised Learning.
Once you finish this course you would have taken a giant leap towards the future of data analysis.

Why Python Machine? 

Machine learning experts have huge employment opportunities

Over 150,000 jobs available in Data Science.

Benefits of Machine Learning:

Job Opportunities
MACHINE LEARNING COURSES IN PUNE

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Course Features
MACHINE LEARNING COURSES IN PUNE

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Topics Covered
  • Types of data
  • Measures of central tendency and dispersion
  • Statistical Graphics
  • Binomial Distribution
  • Poisson Distribution
  • Normal Distribution
  • R Programming
    • Data Types
    • Reading data, Subsetting Data
    • Visualizing the Data
  • Estimation Theory

 

      • Sampling Distribution
      • Point Estimation
      • Interval Estimation

 

  • Testing of Hypothesis

 

    • Inference about one population means
    • Inference about two populations means
    • Analysis of Variance Concept
  • Correlation coefficient
  • Simple Linear Regression
  • Multiple Linear Regression
  • Logistic Regression
  • Moving Average
  • Simple Exponential Smoothening
  • Holt-Winter’s Method
  • ARIMA Models
  • Supervised Learning

 

      • Naïve Bayes Algorithm
      • K-nearest Neigbour Algorithm
      • Decision Trees ( SingleTree )
      • Random Forest
      • Support Vector Machines
      • Linear Discriminant Analysis
      • Neural Network
      • Model Ensembling
        • Bagging
        • Boosting
        • Stacking

 

  • Unsupervised Learning

 

    • Cluster Analysis
      • Hierarchical Clustering
      • K-means Clustering
    • Association Rules Mining
    • Principal Components Analysis
  • Natural Language Processing
  • Term Document Matrix
  • TF-IDF
  • Word Cloud