Machine Learning with Python for Beginners A Step-by-Step Guide with Hands-On Projects Book PDF 2023.

 Machine Learning with Python for Beginners A Step-by-Step Guide with Hands-On Projects Book PDF 2022

The 3 essential steps of machine learning:

Machine Learning is used in artificial intelligence and Analytics and Data Science. 

There are different types of machine learning: supervised, non-supervised and reinforcement. 

Supervised learning: for this learning, we have input data (Features) and the expected result (Label). 

It allows us to make predictions based on a model* that is obtained from historical data and the chosen algorithm. 

Supervised learning attempts to answer two questions: Classification: "what class?"; Regression: "how much?". 

Non-supervised learning: with this learning, you always have features, but no label, because we don’t try to predict anything. 

Based on the historical data we have, we try to see what we can learn from the data, not to mention validate the conclusions obtained with experts in the field. This type of machine learning is typically used to discover structures and models in the data. 

It can also be used for Feature Engineering during the data preparation process for supervised learning (more on this later). 

 Reinforcement learning: With this type of learning, you start with an agent (algorithm) who must choose from a list of actions.

Then, depending on the action chosen, it will receive a return from the environment (from a human in certain situations or from another algorithm):

 it is either a reward for a good choice, or a penalty for a bad action. 

The agent (algorithm) learns which strategy (or stock choice) maximizes the accumulation of rewards. Decomposition of data: Text columns sometimes contain more than one information, so we need to divide them into as many dedicated columns as necessary.

 If some columns represent categories, convert them to category type columns.

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