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why you must stop thinking and begin learning

 why you must stop thinking and begin learning

Can you pick things up quickly enough? It will not suffice to just read and write papers in order to succeed in the future. In order to help others learn from your findings, you must swiftly identify signals and abnormalities in data, unearth hidden information from unstructured sources like text and pictures, build precise models that can be extrapolated from the available data, and publicize your findings. It takes continual attention and deliberate effort to learn quickly; why? because human beings are naturally slow learners. We frequently get stuck in our old routines and habits, which leads us to rely on intuition when we should rely on experiments; trust first impressions when we should trust objective measurements; place too much emphasis on unimportant details when we should focus on important concepts; rely on memory when we should rely on written records; and trust our own words more than those of others. The list is endless, as Albert Einstein once observed:

why you must stop thinking and begin learning

Why you should start studying instead than thinking?

We frequently spend so much time thinking that we entirely forget to experiment and take measurements. We neglect to pay attention to what is actually occurring because we are too preoccupied with thinking about how things should and shouldn't be. A excellent experiment enables us to see inside the black box of our systems, comprehend how they operate, identify their present limitations, and identify possible areas for development. Automated experiments can help us concentrate on the here and now while also providing us with rapid feedback. And that's just one of the reasons you need to put your thoughts on hold and begin studying.

How to stop thinking and start learning?

- Record your experiments. - Keep a record of your observations - Assess your outcomes. - Write down your conclusions - Disseminate your findings - Assess your outcomes - Rerun the procedure. Practice makes perfect; have an open mind; and stay away from typical mistakes.

Try not to understand, but to build something.

Making something yourself is the greatest way to learn. You may assimilate the information better when you construct something and watch your thoughts come to life than if you just read about it from others. So the next time you're struggling to finish a book, try constructing something and see how it works for you. Starting with a modest data set on a matter that interests you or that you want to solve will help you comprehend it better. - To begin evolving, you don't need to comprehend everything; you simply cannot. Start by learning the sections you are familiar with, and then progressively learn the rest. - Your initial implementations only need to function; they don't need to be flawless. - It's not necessary for what you're developing to be prepared for production. - Take a pause if you feel stuck; you don't need to fully comprehend something in order to create it. - You don't need to be an expert to build anything, and you don't need to be flawless to complete it either.

Don’t ask why, ask what?

If you ask "what?" instead of "why," you may concentrate on the important things—what you actually want to learn—since asking "why" might make you grasp just the "why" and never the "what." - A practitioner who wants to know "What information did I miss?" would ask, "What are the reasons why the forecast was wrong," as opposed to an analyst who wants to know "Why did the forecast turn out wrong?" - When putting your thoughts on paper, begin with the "what" and then go on to the "why" if you are certain of the "what" you are attempting to accomplish. - The "what" is the thing you can do, and the "why" is why you should do it. It only makes sense when you know exactly what the "what" is, which is something that can be measured. The "why" is an immeasurable concept.

Don’t ask what, ask who!

Asking "who?" causes us to focus on the people and work that are being done. By doing so, we may learn a lot. For example, if you want to know what a piece of code accomplishes, you can ask who authored it. - You can inquire about the algorithm's creator to see why it produces a certain forecast. - You can ask "who" utilized them if you want to understand another person's perspective or workflow. - Asking who is in charge of a team or organization will reveal how it functions. - Asking "who" employs a specific approach will help you comprehend its benefits and drawbacks. - Asking "who" made a certain decision will reveal the rationale behind it. - You can ask "who" utilizes a particular technology if you want to discover how it functions.

Do not ask “who” and “why”, but “when”

While "what" and "who" usually lead us to anomalies, "why" and "when" frequently lead to generalizations. - Ask when and why a choice was taken if you want to know why it was made. - Ask when a certain technology was created and what it accomplishes if you want to know what it does. - Ask when and why a choice was made if you want to discover who made it and why. - Ask what a piece of code does and when it was created if you want to know what it does. - Ask when and why a certain strategy was used if you wish to comprehend its advantages. - Ask what the dataset represents and when it was gathered if you want to know what it includes. - If you want to discover how a specific issue appears, find out who is impacted by it and when he first encountered it.

Try not to make predictions about the future since there is none!

You just need to comprehend what is occurring right now; you don't need to know what will happen in the future. - Consider yourself an analyst attempting to forecast the demand for a certain product. You could be interested in finding out if the supply chain can keep up with demand or if the marketing team can effectively communicate. - If you attempt to foresee the future and find information like "the marketing team will not be available during the holiday season," you risk producing a false forecast since you are considering a period when your team is not available. - Instead, pay attention to the present moment. Identify the system's bottlenecks and project how they will affect the prediction.


The earlier you begin learning, the better because it is a lifetime process. Starting small, concentrating on the here and now, and building on the information you already have are the keys to quick learning. You can successfully learn as long as you explore, measure, and construct things. You can't go wrong following the recommendations to "read, read, read," "write, write, write," and "build, build, build"; they will get you far. Though it might not be simple, it will be worthwhile.