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Machine Learning(AI Foundation) Certification Training

  • Course Content
  • Drop us a Query

Part 1: Set up

  • Generic Programming Structure, Jupter Notebooks, Tools, Python

Part 2: Regression

  • Simple Linear Regression
  • Multiple Linear Regression
  • Polynomial Regression
  • Gradient Descent
  • Stochiastic Gradient Descent
  • Support Vector Regression (SVR)
  • Decision Tree Regression
  • Random Forest Regression
  • Evaluating Regression Models Performance
  • Hands-on Assignments

Part 3: Classification

  • Logistic Regression
  • K-Nearest Neighbors (K-NN)
  • Support Vector Machine (SVM)
  • Kernel SVM
  • Naive Bayes
  • Decision Tree Classification
  • Random Forest Classification
  • Evaluating Classification Models Performance
  • Hands-on Assignments

Part 4: Clustering

  • K-Means Clustering
  • Hierarchical Clustering
  • Hands-on Assignments

Part 5: Association Rule Learning

  • Apriori
  • Eclat
  • Hands-on Assignments

Part 6: Reinforcement Learning

  • Upper Confidence Bound (UCB)
  • Thompson Sampling

Part 7: Natural Language Processing(Introduction)

Part 8: Deep Learning(Introduction)

  • Artificial Neural Networks
  • Convolutional Neural Networks

Part 9: Dimensionality Reduction

  • Principal Component Analysis (PCA)
  • Linear Discriminant Analysis (LDA)
  • Kernel PCA

Part 10: Model Selection & Boosting

  • Model Selection
  • Interview Prep : Grooming Session
  • Bonus Lecture : Review

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