Sentiments-classification

Sentiment Classification & How To "Frame Problems" for a Neural Network

What You Should Already Know

• neural networks, forward and back-propagation
• stochastic gradient descent
• mean squared error
• and train/test splits

Where to Get Help if You Need it

• Leverage the recommended Course Reading Material - Grokking Deep Learning

Tutorial Outline:

• Intro: The Importance of "Framing a Problem" (this lesson)

  [Curate a Dataset](#lesson_1)
   [Developing a "Predictive Theory"](#lesson_2)
  

• PROJECT 1: Quick Theory Validation

   [Transforming Text to Numbers](#lesson_3)
  

• PROJECT 2: Creating the Input/Output Data

   Putting it all together in a Neural Network 
  

• PROJECT 3: Building our Neural Network

   [Understanding Neural Noise](#lesson_4)
  

• PROJECT 4: Making Learning Faster by Reducing Noise

  [Analyzing Inefficiencies in our Network](#lesson_5)
  

• PROJECT 5: Making our Network Train and Run Faster

  [Further Noise Reduction](#lesson_6)
  

• PROJECT 6: Reducing Noise by Strategically Reducing the Vocabulary

   [Analysis: What's going on in the weights?](#lesson_7)
  

NOTE: unzip file reviews.rar into reviews.txt before run code