Machine Learning

Scope of Machine Learning (ML) is vast, and in the near future, it will deepen its reach into various fields like medical, finance, social media, facial and voice recognition, online fraud detection, and biometrics. Gartner predicts that 30% of Government and large enterprise contracts will require AI-fueled solutions by 2025. Cyber security is another area where we will see huge adoption of ML, which aids multi-layer protection. ML shall also fuel areas that are highly dependent on data.

  • Introduction to Machine Learning
  • Python Basics and Machine learning Package setup
  • Array manipulation
  • Data Wrangling and Manipulation
  • Supervised Learning
  • Regression Models : Linear Models and decision tree
  • Classification Models
  • Introduction to Machine Learning
  • Python Basics and Machine learning Package setup
  • Array manipulation
  • Data Wrangling and Manipulation
  • Supervised Learning
  • Regression: Linear Model, ridge , Decision Tree
  • Classification Models : SVM , RandomForest , K-NN
  • Feature Engineering
  • Gaussian Process
  • Unsupervised learning
  • clustering : K-means and elbow
  • Project : Breast cancer prediction
  • Introduction to Machine Learning
  • Python Basics and Machine learning Package setup
  • Array manipulation
  • Data Wrangling and Manipulation
  • Supervised Learning
  • Regression: Linear Model, ridge , Decision Tree
  • Classification Models : SVM , RandomForest , K-NN
  • Navie Bayes
  • Gaussian Process
  • Feature Engineering
  • Ensemble method
  • Time Series Modelling
  • Recommender Systems
  • Dataset transformations
  • Unsupervised learning
  • clustering : K-means and elbow
  • Manifolds learning
  • Project : sales forecasting for Walmart
  • Wine Quality predictions

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