INDEX

1. INTRODUCTION
   • What is Machine Learning ?
   • What is the use of Machine Learning?
   • How it can be used in real life ? 
   
   

2. BIG DATA
   • What is big Data ?
   • How to handle Big Data ?
   • What is the use of big Data ?
     
     
3. ALGORITHMS
   • Different algorithms and uses.
     
     
4. FEED FORWARD AND BACK PROPAGATION NEURAL NETWORK
   • Feed Forward and Back Propagation Neural Network ( Theory )
   • Feed Forward and Back Propagation Neural Network ( Method/Example )
     
     
5. SUPPORT VECTOR MACHINE
   • Support Vector Machine ( Theory )
   • Support Vector Machine ( Method/Example )
     
     
6. RESTRICTED BOLTZMANN MACHINE
   • Restricted Boltzmann Machine ( Theory )
   • Restricted Boltzmann Machine ( Method/Example )
     
     
7. DEEP LEARNING / DEEP BELIEF NETWORK.
   • Deep Belief Neural Network ( Theory )
   • Deep Belief Neural Network ( Method/Example )
     
     
8. SENTIMENTAL ANALYSIS WITH NAIVE BAYES ALGORITHM
   • Naive Bayes ( Theory )
   • Sentimental Analysis using Naive Bayes Algorithm ( Method/Example )
     
     
9. APRIORI ALGORITHM FOR PREDICTION
   • Apriori Algorithm ( Theory )
   • Apriori Algorithm ( Method/Example )
     
     
10. DECISION TREE ALGORITHM FOR PREDICTION
    • Decision Tree ( Theory )
    • Decision Tree ( Method/Example )
      
      
11. CONVOLUTION NEURAL NETWORK.
    • Convolution Neural Network ( Theory )
    • Convolution Neural Network ( Method/ Example )
      
      
12. RECURRENT NEURAL NETWORK.
    • Recurrent Neural Network ( Theory )
    • Recurrent Neural Network ( Method / Example )
      
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