A Gentle Introduction to Neural Networks for Machine Learning Codementor

We need machine learning for tasks that are too complex for humans to code directly, i.e. tasks that are so complex that it is impractical, if not impossible, for us to work out all of the nuances and code for them explicitly. So instead, we provide a machine learning algorithm with a large amount of data and let it explore and search for a model that will work out what the programmers have set out to achieve. Let's look at these two examples: Then comes the Machine Learning Approach: instead of writing a program by hand for each specific task, we collect lots of examples that specify the correct output for a given input. A machine learning algorithm then takes these examples and produces a program that does the job. The program produced by the learning algorithm may look very different from a typical hand-written program -- it may contain millions of numbers. If we do it right, the program works for new cases, as well as the ones we trained it on. If the data changes, the program can change too by training from the new data. You should note that conducting massive amounts of computation is now cheaper than paying someone to write a task-specific program.