<![CDATA[Sheary Tales's Hub]]>https://sheary.substack.comhttps://substackcdn.com/image/fetch/$s_!_oy1!,w_256,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fb53a3f59-88a3-406c-a878-43a82c5163ae_1218x1218.pngSheary Tales's Hubhttps://sheary.substack.comSubstackTue, 01 Sep 2026 13:32:41 GMT<![CDATA[Machines Learned to Think. They Never Learned to Move.]]>https://sheary.substack.com/p/machines-learned-to-think-they-neverhttps://sheary.substack.com/p/machines-learned-to-think-they-neverSat, 18 Jul 2026 05:51:52 GMTPaid partnership with RISE Robotics.

I spend a lot of time looking at new technology. Most of it is software. And today I come across an innovation in the physical world that makes me stop and rethink how an entire industry works.

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]]><![CDATA[You Don't Need Permission To Build For The World]]>https://sheary.substack.com/p/you-dont-need-permission-to-buildhttps://sheary.substack.com/p/you-dont-need-permission-to-buildMon, 06 Apr 2026 20:34:23 GMT

Let’s be honest, the world has changed.

The next generation of world-changing startups, or products probably won’t just come from offices in San Francisco. They’ll come from someone random like a nurse who got fed up watching patients walk out of appointments more confused than when they walked in. A teacher in a small town who couldn’t get her kids the …

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]]><![CDATA[How Would I Learn This: Part 1 - Find The Right ML Algorithms For Your Problems]]>https://sheary.substack.com/p/how-would-i-learn-this-part-1-findhttps://sheary.substack.com/p/how-would-i-learn-this-part-1-findTue, 03 Dec 2024 10:02:24 GMTThere are wide range of ML algorithms to pick for your problem, from simple linear regression to complex neural networks, it can be overwhelming to get started, especially if you are a self taught.

The challenge here is to understand the problem and the data, breaking it down into manageable components, and identifying the best approach to achieve your goal.

The process of selecting a machine learning algorithm is not a one-size-fits-all task. It involves defining the type of problem, analysing the data, and matching the problem's characteristics with the most suitable algorithm.

This article will guide you through a 5-step framework I’ve learned for finding the right machine learning algorithm for your task:

  1. Define the type of task you are solving.

  2. Understand the machine learning category it falls under.

  3. Explore and analyze your data (EDA).

  4. Identify the specific variation of your problem and determine the appropriate algorithm.

  5. Match the problem to the algorithm.

Let’s dive in!

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]]><![CDATA[How Would I Learn Javascript: My 5 Effective Self Taught Approach]]>https://sheary.substack.com/p/how-would-i-learn-javascript-my-5https://sheary.substack.com/p/how-would-i-learn-javascript-my-5Thu, 28 Nov 2024 21:30:31 GMT

This is one of the requests I have received a lot, how to study Javascript? Do you have any roadmap?

You know what is Javascript, it is one of the most essential programming languages in the world, powering millions of websites and applications, mostly for the front end, but backend can be done too (NodeJS).

But learning JavaScript can feel overwhelming, especially with countless tutorials and endless concepts to explore. Where do you even begin?

This guide is here to simplify the process. By focusing on the fundamentals, asking the right questions, and applying what you learn through hands-on practice, you'll gain a solid foundation in JavaScript and the confidence to start building your own projects.

From understanding core concepts like variables and functions to creating your first small project, this roadmap will help you master the basics and think like a true problem-solver.

Ready to get started?

Let’s dive in!

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]]><![CDATA[How I would learn Supervised & Unsupervised Learning: Self Taught Approach.]]>https://sheary.substack.com/p/how-i-would-learn-supervised-andhttps://sheary.substack.com/p/how-i-would-learn-supervised-andSun, 24 Nov 2024 17:39:55 GMTHi there, it’s your self taught Codersheary :) 🙋‍♀️

Understanding supervised and unsupervised are crucial to understand machine learning, deep learning and LLM. At its core, machine learning is about teaching machines to learn patterns from data, similar to how human brains interpreted information around the us.

For self-taught learners, it can feel daunting to understand technical jargon without first grasping the basic concepts. What does "supervised" and "unsupervised" actually mean, and how do they apply to machine learning?

This guide is designed to simplify the concepts and walk you my approach in understanding these two essential types of machine learning.

This article breaks down the concepts into simple, actionable steps to help you understand what supervised and unsupervised learning are, how they work, and why they matter. By starting with their basic definitions, and then the fundamentals of its inner workings, and exploring their real-world use cases, you would gain the tricks on how I learned the topic.

Let’s get started with one of the most important topic in machine learning!

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]]><![CDATA[How Would I Learn SQL: A Step-by-Step Guide with Projects.]]>https://sheary.substack.com/p/learn-sql-fundamentals-in-a-weekendhttps://sheary.substack.com/p/learn-sql-fundamentals-in-a-weekendWed, 20 Nov 2024 14:51:01 GMTNow that you have the front end ready for your project, it’s time to focus on one of the most crucial aspects: the database. This is where you’ll store user information, transaction data, products, user activities, and more.

Personally, I prefer building my own database over using no-code solutions because it offers greater scalability as the application grows.

In the future, I plan to write another guide that dives into advanced SQL topics.

For now, here’s my 5-step roadmap to mastering the fundamentals of SQL over a weekend. It includes a small project with answers.

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]]><![CDATA[5 Minutes Explain: Explain Overfitting, Training Set, Test Set]]>https://sheary.substack.com/p/5-minutes-explain-explain-overfittinghttps://sheary.substack.com/p/5-minutes-explain-explain-overfittingFri, 21 Jun 2024 15:20:38 GMT

Machine learning models learned and trained from big dataset in order to output a predictions.

But we don’t just want a prediction, we want the CORRECT prediction.

So how do make our ML model does that?

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]]><![CDATA[Gradient Descent For Beginners]]>https://sheary.substack.com/p/gradient-descent-for-beginnershttps://sheary.substack.com/p/gradient-descent-for-beginnersWed, 01 May 2024 17:13:35 GMTGradient: You.

Descent: Moving downhill.

Gradient Descent: You trying to find the best way to move downhill.

In machine learning:

Gradient: A slope of a straight line.

Descent: Moving downwards.

Gradient Descent: An algorithm used in machine learning and deep learning to find the minimum point of a function (by iteratively moving towards the optimal set of pa…

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]]><![CDATA[Deep Learning 003: Hands-on calculating perceptron weight]]>https://sheary.substack.com/p/deep-learning-003-hands-on-calculatinghttps://sheary.substack.com/p/deep-learning-003-hands-on-calculatingWed, 27 Mar 2024 10:58:46 GMT

In our Deep Learning 001 we talked about adding weight to our input value to produce the result y, but what is weight? What is it important in deep learning?

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The Supervised Learning Scenario

So let me briefly explain to you what is supervised learning.

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]]><![CDATA[Deep Learning 002: Vector Matrix Multiplication]]>https://sheary.substack.com/p/deep-learning-002-vector-matrix-multiplicationhttps://sheary.substack.com/p/deep-learning-002-vector-matrix-multiplicationFri, 22 Mar 2024 13:54:35 GMTAs we can see from our previous post, a perceptron consists of x multiplied w we will get y.

But not a scalar variable of x (scalar means 1 single number) or w, there are more than one.

What if we can arrange them into something like this:

These are vectors.

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]]><![CDATA[Deep Learning 001: 5 Mins To Understand Perceptron]]>https://sheary.substack.com/p/deep-learning-101-3-mins-to-understandhttps://sheary.substack.com/p/deep-learning-101-3-mins-to-understandSun, 17 Mar 2024 16:06:59 GMTThe perceptron

A perceptron is a type of artificial neuron.

The input can be x1, x2, x3 and so on. The weight indicate how important is the x.

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]]><![CDATA[I Self Teaching Data Analytics for fun – my few months journey so far + resources]]>https://sheary.substack.com/p/i-self-teaching-data-analytics-forhttps://sheary.substack.com/p/i-self-teaching-data-analytics-forSat, 11 Feb 2023 08:46:24 GMTHello February!

I hope you are well! It is only February and we have already heard a lot of tech news about the most recently AI invention: ChatGPT launched, Google released BARD, Elon Musk Twitter Disaster, big techs layoffs etc.

There will be more news coming up in the next few months, so sit tight, and stay tuned everyone 🤣

New site launched (beta)

So recently I have announced about sharing data analytics resources on my newsletter.

And here it is!

I will be sharing the resources on my new website (still developing 🤣), have a look!

Here is the link

I will also be sharing more resources and contents on the website, please keep an eye on it 👀

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]]><![CDATA[Learn to fetch data with MongoDB in 10 mins!]]>https://sheary.substack.com/p/learn-to-fetch-data-with-mongodbhttps://sheary.substack.com/p/learn-to-fetch-data-with-mongodbTue, 09 Aug 2022 03:05:38 GMTListen to the audio above for my warm introduction 😋

So today we are going to talk about:

  1. What is MongoDB? What does it look like? Different ways to fetch data with MongoDB.

  2. Some funny images I have generated using Dall.E

  3. MongoDB study resources.

What is MongoDB?

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]]><![CDATA[✨Learn Programming & Build Projects in 5 Months (Python version)]]>https://sheary.substack.com/p/learn-programming-and-build-projectshttps://sheary.substack.com/p/learn-programming-and-build-projectsWed, 08 Jun 2022 02:49:36 GMT🚧 This post is a bit lengthy… View it in browser 🚧

It has been awhile…

Hello my friend, how are you?

It has been months since my last newsletter.

The past few months have been hectic for me: launching the MVP for my projects, looking for team members, working on the newer version of my project etc.… I have no choice but to pause my newsletter and all my media thingy for a while.

After a week of a short vacay, I am back to provide you with more tech contents and inspiring things.

Today’s Newsletter

So in this newsletter I am going to introduce you my way of learning new programming languages or technology.

Basically to learn anything.

If you are a total beginner, you are at the right place.

For the past 2 months I was mentoring a total beginner to get started in programming and how to learn Python quickly.

And now he has been progressing a lot, he is able to find projects to build and solve problems himself.

Guidance is great!

But remember, everything is all about being able to google things yourself and solve problems independently,  you don't have to master everything.

This is the outcome you want: not to rely on guidance from others, you gotta craft your own path.

Anyway, let’s get started.

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]]><![CDATA[21 Uncommon Questions Asked By Self Taught Programmers | My Daily Routine.]]>https://sheary.substack.com/p/21-uncommon-questions-asked-by-selfhttps://sheary.substack.com/p/21-uncommon-questions-asked-by-selfWed, 02 Mar 2022 04:06:58 GMTDear my lovely lovely subscribers, hello!

I am back with a YouTube playlist you might be interested:

WATCH THE VIDEO HERE

This playlist is on YouTube feel free to share it or watch it anytime!

Also please let me know for any contents you would love to see more.

Share Sheary’s Newsletter

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]]><![CDATA[Few Things Might Happen In The Year of 2041.]]>https://sheary.substack.com/p/few-things-might-happen-in-the-yearhttps://sheary.substack.com/p/few-things-might-happen-in-the-yearThu, 17 Feb 2022 13:42:53 GMTHello my friend, hope you are well!

It’s my birthday today and I was supposed to be going for an islands hoping trip, unfortunately due to the rising Covid cases we have no choice but to postpone the plan :’(.

Thank you for reading my newsletter 😊. This post is public so feel free to share it.

Share

Anyway I was just sharing haha!

Today we are going to discus…

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]]><![CDATA[Good news!! 😍 And what's your recommended learning resources?]]>https://sheary.substack.com/p/good-news-and-whats-your-recommendedhttps://sheary.substack.com/p/good-news-and-whats-your-recommendedWed, 26 Jan 2022 02:42:54 GMTHello everyone! Today newsletter is going to be short don’t worry…

For those who had experienced some difficulties subscribing to the paid version, apologize for that! Indeed I was facing some difficulties regarding the payment methods here on Substack…

Which means I am going to continue sending you free newsletter for now, you will receive informational …

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]]><![CDATA[Money vs Passion: Achieving the new wealth by doing what you love.]]>https://sheary.substack.com/p/money-vs-passion-achieving-the-newhttps://sheary.substack.com/p/money-vs-passion-achieving-the-newThu, 20 Jan 2022 01:09:01 GMTNOTED: PAYMENT IS NOT WORKING AT THE MOMENT, WILL BE BACK ONCE IT HAS BEEN RESOLVED!

I will still be writing every week so no rush you will be able to read it soon 😍

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]]><![CDATA[Book Recommendations: Tech, ML, Programming, Startups, Business, Self Motivation, UI&UX and more]]>https://sheary.substack.com/p/book-recommendations-tech-ml-programminghttps://sheary.substack.com/p/book-recommendations-tech-ml-programmingWed, 12 Jan 2022 14:40:10 GMTTLDR;

This email is going to be long so it is preferable to read it on the website.

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]]><![CDATA[2022 Tech Trends. How To Predict The Future?]]>https://sheary.substack.com/p/2022-tech-trends-how-to-predict-thehttps://sheary.substack.com/p/2022-tech-trends-how-to-predict-theWed, 05 Jan 2022 04:54:21 GMTHappy new year! I wish you have an amazing week so far. Everyone has been talking about their new year resolutions. What’s yours?

New year, new life! Let’s talk about the big tech trends people have been talking about on the internet.

Today’s newsletter is going to be shorter than the previous one I promised haha!

How to predict the future

Well, I have no …

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