Decision making is not about the past, but about the future intrinsically. On the other hand, the essence of the future lies in uncertainty. So, decision making is something about uncertainty. Uncertainty means unpredictability, which means it is random.v

The randomness of this unpredictability can be expressed in other forms of randomness. It is the randomness expressed on the probability distribution. Suppose you toss a coin 100 times and count the number of heads that appear. The reason you are doing this probability experiment is to determine (inference) and determine that the coins used to toss are not balanced. It is reasonable to believe that the number of heads appearing 90 or 15 is statistical evidence that the coin is not balanced.

However, where should the boundary line be drawn for making such statistical inferences? Is the number of heads appearing 77, 65, or 55? We cannot draw any conclusions from a sample of 100 tossing a coin without knowing the distribution of probability that a balanced coin will appear heads.

The obvious and only purpose of what we see, learn and learn is to make it our own. Scientific thinking is a "skill" that is not easy to make on your own. It's beyond ordinary...

The obvious and only purpose of what we see, learn and learn is to make it our own. I don't just have it as an idea in my head, but I want to use it in the real world.

So, we “train” it to make it our own. If you want to take it in a short time, and if it is knowledge in text form, you can see it over and over and try to solve the problem and make it completely mine. Or you can get it at some point by accumulating and accumulating over a long period of time without intensive effort.

The expressions “I know with my heart, not my head, I know with my body,” are possible expressions when it is embodied as my own.

Whether it's mental or physical, being completely mine is nothing more than neuronal cell bodies and neurons forming a network in the brain, according to research in brain science. Being completely mine from the perspective of brain science is nothing more than a physical thing.

Scientific thinking is a "skill" that isn't easy to do on your own. It is thought that some kind of genius ability beyond the ordinary should be endowed. Just like Sherlock Holmes.

However, the current process of seeing texts about scientific thinking with your eyes and thinking with your head is the process in which nerve cells and neurons form a network of “scientific thinking” in the brain. A genius may not know it, but ordinary people like us will accumulate and accumulate such processes and at some point acquire such abilities.

In the process of constantly reading related articles, your head will start thinking at that moment, and you can gradually deepen your inner workings. That way, you will test it when you occasionally encounter situations in the real world. In doing so, I can make it more and more my own. The information network of neurons for scientific thinking will be fully formed in the brain.

Scientific thinking, namely Sherlock Holmes, Father Brown, Dupin, and Hannibal, such as Zhuge Resonance, can be compared as people who studied mind, but in any case, their extraordinary abilities can enrich our lives.

Let's try it out and use it on an interpersonal object.

A person who practices it in the real world is Dr. Goldlett, a physicist and business scientist. In order to systematize the thought process, Goldlet practiced and researched more than 200 times of linking real-world business and everyday problems with facts observed on paper in a causal relationship. In the process, he was able to obtain necessary and good theories and solutions to problems.

He uncovered numerous "errors" that had been adorned with authority and theory, and enabled us to awaken the thinking that had been dominated by authority and theory. He was able to get a way to prove the right thing, not from authority and theory, but from "the logic inherent in the situation." Since the discovery of arithmetic calculations by the American Management Accounting Association (IMA), this is the background to the emergence of a "thinking process" theory called the Thinking Process, which has been evaluated as the most important "intellectual achievement" of mankind. ASAM TESTING

Making it mine means that the neurons in the neuronal cell body form a network, and the process of thinking about scientific thinking while reading this article is the process of neurons forming a network. For "scientific thinking," neuron cells are interconnected information networks. "Scientific thinking" is also a methodology by which we can give each other "intellectual stimulation".

On March 9, 2016, a shocking incident occurred in which Go player Sedol Lee lost against Google's artificial intelligence (AI) AiphaGo. People who don't usually play Go, those who have nothing to do with the IT industry, and those who think that artificial intelligence is a subject that only appears in movies and cartoons also paid attention to this. This process is reflected in the documentary.

AiphaGo was implemented by deep learning, which is the core technology of artificial intelligence, and was an opportunity to spark interest in deep learning in the general public after the match with Sedol Lee. On the other hand, machine learning, machine learning as an artificial intelligence technology has also begun to be recognized by the public, and the relationship between artificial intelligence, machine learning, and deep learning can be summarized as follows.

Machine learning belongs to a large category of artificial intelligence, and a part of machine learning is classified as deep learning. By analogy, artificial intelligence corresponds to general food, machine learning corresponds to more advanced food, and deep learning corresponds to high-end steak dishes. Therefore, the flower of artificial intelligence can be called deep learning. This does not mean, however, that other technologies in machine learning other than deep learning are useless. It's just the choice of which technology to apply to the situation is different. Naive Bayes algorithm, a type of machine learning technology, is typically applied to the technology of filtering spam in the mail space we encounter every day.

In this series, we want to focus on Bayesian inference underlying deep learning and artificial intelligence technologies. The basis of deep learning is an artificial neural network. Although the Bayesian Neural Network model, which has recently evolved an artificial neural network, is attracting attention, it focuses on artificial neural networks and Bayesian inference itself.

Everyone talks about artificial intelligence. My Facebook news feed is also covered with artificial intelligence content. Articles related to artificial intelligence account for a significant portion of newspapers, and electronic products need to include the term artificial intelligence to sell well. There is even a joke that if you enter the word artificial intelligence in your business plan, you can receive investment. Although this is likely to cause controversy over bubbles, artificial intelligence, especially deep learning, is proving itself day by day by putting out amazing results to the world. In addition, many artificial intelligence software libraries have emerged, becoming a world where even general software developers can easily use artificial intelligence. However, there was a time when artificial intelligence was reserved only for 'doctors'. This is because the theoretical structure of these artificial intelligence technologies is very mathematical and specialized, so it is theoretically overkill for the general public and general software developers.

However, if this series is for general developers, it will mainly be filled with contents about libraries and source code fragments such as Python, Anaconda, TensorFlow, and Keras. The main purpose is to explore the content itself of artificial intelligence rather than to explore what kind of story these technologies consist of and how they work. There will be some mathematical and technical content, but there will be no need to worry at all as it will be developed with common sense content so that ordinary business people can fully understand and access it.