Python Guide: Clear Introduction to Python Programming and Machine Learning PDF 2023.

 Python Guide: Clear Introduction to Python Programming and Machine Learning PDF 2023.

What is machine learning?

Machine learning or machine learning is a sub-discipline of artificial intelligence that consists of detecting trends within a knowledge history (example: the climate) in order to derive a prediction model for the future (here, the weather). 

 How does machine learning work? Machine learning (ML) is one of the main artificial intelligence technologies. It consists in training an algorithm to recognize recurrent patterns within a learning base. This training results in a computer model designed to make predictions (recognize a sound, an image...) or automate tasks (answer a question, automate the driving of a vehicle...). 

 Where a traditional program executes instructions, a machine learning algorithm improves its performance as it learns, but also as the context evolves and successive re-trainings. 

The more data we "feed" it, the more accurate it becomes. In the 2010’s, machine learning achieved momentum with the advent of big data and the progression of computing capabilities (including the rise of GPUs). 

Indeed, big data is essential to train models on the vast volumes of data needed for automatic language processing or image recognition. What is a machine learning model? A machine learning model is a file that has been trained from a learning base in order to automate tasks, for example to recognize an emotion with regard to an expression on a face, translate a text, propose products according to an appetite profile... Once trained, the model must be able to generate results from data (texts, photos) that it has never processed before. 

 What is the value of machine learning? 

 Its most popular applications in this area include product recommendation, machine translation, autonomous vehicles and diagnostic assistance in the health sector. Within massive volumes of data, machine learning also makes it possible to detect hidden trends, which are not detectable via human analysis.

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