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Most companies have already faced the need to use digital solutions to optimize internal and external business processes. According to… As Artificial Intelligence (AI) is on the rise, more and more companies are looking for ways to incorporate this technology… In the modern world, technology has become integral in our lives and has led to the rise of the knowledge… Training the right approach to self-education can be difficult. Many people think that self-education is simply a matter of downloading…
How to Learn Programming Properly: The Franklin Method The main problem in self-learning is the lack of a systematic approach. It is difficult to know what to teach first and what second, and in what order. Self-study The self-taught path is a “poke method", communication on forums, searching for like-minded people, going to conferences and get-togethers-meetups. This is the way of the samurai. The path is not suitable for everyone. Therefore, for the broad masses, a bunch of self-instruction manuals were released – thousands of books, similar to each other like twins. The self-instruction book is good because it quickly immerses you in the topic. You will start coding almost the day you open the book. But there is one problem, says MIT professor James Koppel: These books don’t teach you anything. The main thing is there are long code listings that the reader must reproduce. As in university lecture notes, “the code moves from the book page to the reader’s screen, bypassing the brain." Students who listen to regular lectures are 55% more likely to fail the exam than those who participated in the discussion of the material, even if only slightly. Franklin’s method In order to get some benefit from tutorials or lectures, some experts recommend performing practical exercises in a special way. It can be called the Franklin method. This method is very simple in practice. Read the book as usual. When you come across a sample code, read it. Close the book. Try to dial the code. Repeat steps 1-3. The point is to internalize mental images – propagation-sensitive data structures. In this case, the brain works like an autoencoder in machine learning. “An autoencoder is a neural network that tries to output the same data as the input, but pass through an intermediate layer that is too small to fully represent the data. During this procedure, he teaches a more compact representation of the data. Here, the neural network is a collection of dendrites in your head, ” – writes James Koppel.
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