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Machine Learning Training in Jaipur

  • Machine Learning

    Zeetron Networks is one of the top companies of Jaipur providing Machine Learning Training Course. The training provided is at par with current industry standards which helps one to achieve their goals and their dream jobs in top companies of the world.

    Machine Learning is considered a part of Artificial Intelligence in the field of Computer Science. It often uses statistical techniques to give computers the ability to “learn” ( progressively enhance the performance of a particular task) with data, without being specifically programmed. Machine Learning is often related to computational statistics, which also concentrates on prediction -making through the use of computers.

  • Why Choose Us For Machine Learning?

    • Our Team caters the need, therefore, it provides nation-wide recognized certification to its students after the completion of their machine learning training Training.
    • We conduct Machine learning training classes in highly built latest smart labs with all necessary learning equipment.
    • It conducts online Machine learning training courses for making the learning experience more worth.
    • For engineering students who wish to build their career and want to learn something more valuable other than there course in their holidays, we host industrial training in Machine learning.
    • we provide the best corporate training in Machine learning to working professionals for improving skills in the technology of their want.
    • Variable time slots according to the student’s suitability.

Course Content

  • What is machine learning?
  • What is the use case of Machine learning?
  • Statistical learning vs. Machine learning
  • Iteration and evaluation
  • Major Classes of Learning Algorithms -Supervised vs Unsupervised Learning
  • Different Phases of Predictive Modelling (Data Pre-processing, Sampling, Model Building, Validation)
  • Concept of Overfitting and Underfitting (Bias-Variance Tradeoff) & Performance Metrics
  • Types of Cross-validation(Train & Test, Bootstrapping, K-Fold validation, etc)
  • Introduction to CARET package
  • Introduction to H2O package
  • Linear Regression
  • Logistic regression
  • Generalization & Non Linearity
  • Recursive Partitioning(Decision Trees)
  • Ensemble Models(Random Forest, Bagging & Boosting(ADA, gbm etc))
  • Artificial Neural Networks(ANN)
  • Support Vector Machines(SVM)
  • K-Nearest neighbors
  • Naive Bayes
  • K-means clustering
  • Challenges of unsupervised learning and beyond K-means
  • Market Basket Analysis
  • Collaborative Filtering
  • Social Media – Characteristics of Social Media
  • Applications of Social Media Analytics
  • Metrics(Measures Actions) in social media analytics
  • Examples & Actionable Insights using Social Media Analytics
  • Text Analytics – Sentiment Analysis using R
  • Text Analytics – Word cloud analysis using R
  • Text Analytics - K-Means Clustering
  • Introduction of JAQL Approach
  • Understand the information stream
  • Understand Information ocean
  • Working with JAQL Language
  • Understand Data WareHousing
  • The requirement of Data Warehousing
  • Data Warehousing with Hive
  • Understand the Hive environment
  • Working with Hive Query Language
  • Perform DDL approach Through Hive
  • Perform a DML approach through Hive
  • Introduction of PIG
  • Requirement of Pig
  • Working with pig Script
  • Running and managing Pig Script
  • Perform Streaming Data Analytics through PIG
  • Pig Advantages and Disadvantages
  • Understand Flume methodology
  • Requirement of flume
  • flume advantages
  • working lab with flume
  • introduction of Sqoop
  • Requirement of Sqoop
  • advantages of Sqoop