I’ve now begun my 1000 mile journey to get familiar with Artificial Intelligence. There are so many aspects of AI: Natural Language Processing (NLP), Computer Vision, Robotics, Machine Learning and so on. I can see my journey taking me a good number of years. I have to familiarise myself with High School and University Math and Stats.
Here is what I’ve gotten on Machine learning (ML) so far. It entails a three-step process: Data > Model > Action. You put in training data into your model, and when it is sufficiently “taught”, you put it into action with real-world data.
Machine Learning is distinct from Data Mining, though they both have similarities, such as using inferential methods to draw conclusions. Data mining is about cleaning up large data sets to find patterns. It is much more of a manual process. Machine learning tries to uncover the patterns in new data through experience derived from previous data (the training set). Once there is confidence that the model will (almost) accurately find the patterns in any data set, you release it out in the wild.
A book I am going through is Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition). I’ve gone through 2 chapters and can recommend it as you start your journey.
