Machine Learning

by ABC Training Claim Listing

Machine learning is an area of artificial intelligence and computer science that covers topics such supervised learning and unsupervised learning and includes the development of software and algorithms that can make predictions based on data.

$19259

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img Duration

96 Hours

Course Details

Machine learning is an area of artificial intelligence and computer science that covers topics such supervised learning and unsupervised learning and includes the development of software and algorithms that can make predictions based on data.

Machine Learning is implemented where programming or developing an efficient algorithm is problematic or not feasible. Machine Learning is revolutionizing the computing ecosystem.

 

Course Objectives:

The objective of this training program is to understand how machines can learn from its past experience which is considered as the core of AI. We focus on creating strong fundamental knowledge sets on building algorithms by mastering the principles of statistical analysis.

 

Roles In Industry:

  • Machine Learning Engineer
  • Data Scientist- Machine Learning/NLP
  • Data Engineer- Machine Learning
  • Architect
  • Natural Language Processing Engineer-Machine Learning
  • Machine Learning Software Engineer
  • Data Scientist-Advanced Analytics
  • Data Analyst-Machine Learning
  • Machine Learning Specialist
  • Lead Data Scientist
  • Machine Learning Developer
  • Engineer-Machine Learning
  • Artificial Intelligence Expert
  • Consultant
  • Research Engineer
  • Software Engineer-Machine Learning
  • Manager-Machine Learning & Analysis

 

Course Highlights:

  • Introduction to Machine Learning
  • Programming with R
  • R based projects development
  • Programming with python
  • Python based projects development
  • Statistics Essentials
  • Knowledge extraction using Statistics Essentials
  • Pre program preparation
  • Supervised Learning
  • Classification Algorithms
  • Regression Algorithms
  • Unsupervised Learning
  • Deep learning(Neural Networks)
  • Data Analysis
  • Text mining and NLP

 

What You'll Learn?

  • Intro to Machine Learning and R programming.
  • Stats preliminaries, Data types, Central Tendency.
  • Normal Distribution, Skewness, Kurtosis, Q-Q plot.
  • Binomial & Poisson Distributions, Correlation Analysis.
  • Confidence Interval, Z & T-distributions, Case Study.
  • Confusion matrix, Precision, Recall, F-score.
  • Classification algorithms: Decision Tree, GINI.
  • Entropy, KNN, Case Study.
  • SVM, Naïve Bayes Classifier, Case Study.
  • Logistic & Linear Regression, Case Study.
  • Aurangabad Branch

    Near Jama Masjid, H No 5-1-44/4, Aurangabad

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