WEEK 7

WEEK 7

1. Introduction to Machine Learning

   • Use Python in the context of machine learning
   • Machine Learning is often associated with AI, artificial intelligence, and especially robots in science fiction movies

2. Image Classification with Python

   • Now apply these principles to recognizing digits
   • Sklearn is a module for machine learning. this module comes with a few standard datasets, such as the digital dattaset

3. Nearest Neighbors with Python

   • In Python, we don't need to define the type of variable, or differentiate between single and double quotes.

4. Image Classification

   • With an image of a digital, we can map the grayscale value of eachpixel to a numbre, and each number to a dimension.

5. Text Clustering

   • We’ll be using unsupervised learning
     • More specifically, given a set of unlabeled points, our algorithm will group them into k groups
       • His algorithm is called k-means, the details of which are beyond the scope of this class

6. More iImage Classification

   • Challenges to image recognition include the following:
     • Image recognition algorithms can be improved by grouping pixels in an image into feature, in a process called deep learning
     • A lot of computational power is needed for these algorithms, and libraries like TensorFlow help build programs that use machine learning to solve some problem.
     • The Deep Dream Generator also finds patterns in input images, and combines them together, so that we might get a photo mixed with the style of a painting.