TechVibe
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I'm Eyob, a self-taught dev sharing my Tech journey, tips, tools, and real-world projects. Let’s grow together😊

DM for any project ideas @alnova19

Personal site: https://eyobsimachew.vercel.app
My Github: https://github.com/Eyob-smax
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TechVibe pinned Β«I was reviewing my summer goals, these were my goals    - making 50k birr from       my day job    - building 3 cool project    - stay consistent on gym workout    - finish react master      class course. And turns out    - I made over 60k from     β€¦Β»
If you don't know where to download AI models for your application, then they are easy to download from here.

```ollama pull llama3.2```

This is a large, unique collection of popular AI models for downloading.
You can also use Ollama to download AI models local to use ai without internet

#TechVibe #AI @alnova19
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By the way, talking with someone in their 60s or 70s who’s educated is such an underrated quality time fr 😊

#TechVibe @alnova19
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Coding is tricky. Coding in interviews feels even harder. It’s intimidating, uncertain and hard to prepare. Here are 4 ways to do it!

1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/

2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/

3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf

4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/


#TechVibe #coding resources @alnova19
One of the best day ever fr😊
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Forwarded from YearProgressET
β–“β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘ ፩% (1%)
Forwarded from Dagmawi Babi Jobs
Join the Prime Intellect RL Residency

Apply here
β€’ form.typeform.com/to/ibQawo5e

The RL Residency gives you:
β€’ Compute for experiments
β€’ A stipend
β€’ Hands-on support from our internal research team

Who should apply?
β€’ Grad students with research ideas
β€’ Independent builders & hackers
β€’ Part time researchers exploring novel RL environments and evals

If you’ve wanted to build environments but lacked compute or support - this is for you

@DagmawiBabiJobs
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My typings after AIπŸ˜‚

#TechVibe @alnova19
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Last day before heading back to campus ✨😊

#TechVibe #LastBreakDay @alnova19
My IDE is my safest place to be πŸ’»πŸ˜Ž

#TechVibe @alnova19
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The Grade 12 exam results will be released the day after tomorrow.
I created @ResultsRobot two years ago to help students access their results, and it will be available again tomorrow to assist everyone.

Please note that this is an unofficial service. I built it as an alternative to the official site, which often becomes overloadedβ€”along with the official Telegram botβ€”when hit by a massive number of students all at once.


#esubalew #grade12
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I experience this every time I go to an office, especially government-related ones. Even for really small tasks, the officials take about an hour. This is such an annoying habit. I think they’ve adapted to it so much that it has become part of their routine. But it only makes things messy and wastes our precious time.

I honestly don’t understand them. How do they make things this hard? I even thought people like this must be among the most depressed in their lives, because how can someone be this cruel? I can’t even imagine it.


For me, this is one of the biggest problems in Ethiopia, because I move fast and don’t like wasting time.

#TechVibe @alnova19
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Forwarded from Chapi Dev Talks
Don't despise your "ugly" code.

Nobody looks at a caterpillar and judges it for not being a butterfly yet. We understand it's in a state of progress. πŸ›

Apply that same grace to yourself.

In tech, art, or any field, the path to mastery is paved with early drafts, failed attempts, and constant learning. That's not failure; it's transformation. Embrace the journey from caterpillar to butterfly.

Your most adorable work is yet to come.

Happy hacking fellas
Master Javascript :

The JavaScript Tree πŸ‘‡
|
|── Variables
| β”œβ”€β”€ var
| β”œβ”€β”€ let
| └── const
|
|── Data Types
| β”œβ”€β”€ String
| β”œβ”€β”€ Number
| β”œβ”€β”€ Boolean
| β”œβ”€β”€ Object
| β”œβ”€β”€ Array
| β”œβ”€β”€ Null
| └── Undefined
|
|── Operators
| β”œβ”€β”€ Arithmetic
| β”œβ”€β”€ Assignment
| β”œβ”€β”€ Comparison
| β”œβ”€β”€ Logical
| β”œβ”€β”€ Unary
| └── Ternary (Conditional)
||── Control Flow
| β”œβ”€β”€ if statement
| β”œβ”€β”€ else statement
| β”œβ”€β”€ else if statement
| β”œβ”€β”€ switch statement
| β”œβ”€β”€ for loop
| β”œβ”€β”€ while loop
| └── do-while loop
|
|── Functions
| β”œβ”€β”€ Function declaration
| β”œβ”€β”€ Function expression
| β”œβ”€β”€ Arrow function
| └── IIFE (Immediately Invoked Function Expression)
|
|── Scope
| β”œβ”€β”€ Global scope
| β”œβ”€β”€ Local scope
| β”œβ”€β”€ Block scope
| └── Lexical scope
||── Arrays
| β”œβ”€β”€ Array methods
| | β”œβ”€β”€ push()
| | β”œβ”€β”€ pop()
| | β”œβ”€β”€ shift()
| | β”œβ”€β”€ unshift()
| | β”œβ”€β”€ splice()
| | β”œβ”€β”€ slice()
| | └── concat()
| └── Array iteration
| β”œβ”€β”€ forEach()
| β”œβ”€β”€ map()
| β”œβ”€β”€ filter()
| └── reduce()|
|── Objects
| β”œβ”€β”€ Object properties
| | β”œβ”€β”€ Dot notation
| | └── Bracket notation
| β”œβ”€β”€ Object methods
| | β”œβ”€β”€ Object.keys()
| | β”œβ”€β”€ Object.values()
| | └── Object.entries()
| └── Object destructuring
||── Promises
| β”œβ”€β”€ Promise states
| | β”œβ”€β”€ Pending
| | β”œβ”€β”€ Fulfilled
| | └── Rejected
| β”œβ”€β”€ Promise methods
| | β”œβ”€β”€ then()
| | β”œβ”€β”€ catch()
| | └── finally()
| └── Promise.all()
|
|── Asynchronous JavaScript
| β”œβ”€β”€ Callbacks
| β”œβ”€β”€ Promises
| └── Async/Await
|
|── Error Handling
| β”œβ”€β”€ try...catch statement
| └── throw statement
|
|── JSON (JavaScript Object Notation)
||── Modules
| β”œβ”€β”€ import
| └── export
|
|── DOM Manipulation
| β”œβ”€β”€ Selecting elements
| β”œβ”€β”€ Modifying elements
| └── Creating elements
|
|── Events
| β”œβ”€β”€ Event listeners
| β”œβ”€β”€ Event propagation
| └── Event delegation
|
|── AJAX (Asynchronous JavaScript and XML)
|
|── Fetch API
||── ES6+ Features
| β”œβ”€β”€ Template literals
| β”œβ”€β”€ Destructuring assignment
| β”œβ”€β”€ Spread/rest operator
| β”œβ”€β”€ Arrow functions
| β”œβ”€β”€ Classes
| β”œβ”€β”€ let and const
| β”œβ”€β”€ Default parameters
| β”œβ”€β”€ Modules
| └── Promises
|
|── Web APIs
| β”œβ”€β”€ Local Storage
| β”œβ”€β”€ Session Storage
| └── Web Storage API
|
|── Libraries and Frameworks
| β”œβ”€β”€ React
| β”œβ”€β”€ Angular
| └── Vue.js
||── Debugging
| β”œβ”€β”€ Console.log()
| β”œβ”€β”€ Breakpoints
| └── DevTools
|
|── Others
| β”œβ”€β”€ Closures
| β”œβ”€β”€ Callbacks
| β”œβ”€β”€ Prototypes
| β”œβ”€β”€ this keyword
| β”œβ”€β”€ Hoisting
| └── Strict mode
|
| END __

#TechVibe #JavaScript @alnova19
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πŸ“š 10 of the best free books in the field of data science
πŸ“‘ that you should include in your learning program!

1️⃣ Python Data Science Handbook
Using unique Python libraries with a focus on data science.
Link: PDF


2️⃣ Hands-On Machine Learning book
This book explains the concepts of machine learning with practical examples and Python code and is suitable for novice programmers.
Link: PDF


3️⃣ Deep Learning book
The best book for machine learning and deep learning written by 3 active and top researchers in these fields.
Link: PDF


4️⃣ R for Data Science book
This book reflects the best ways to use R in data science.
Link: PDF


5️⃣ Data Science from Scratch book
This book starts from the simplest possible level and provides you with all the necessary tools and skills to become a great data scientist.
Link: PDF


6️⃣ Machine Learning Yearning book
Error detection in machine learning projects.
Link: PDF


7️⃣ Bayesian Methods for Hackers book
Practical applications of Bayesian inference and probabilistic programming.
Link: PDF


8️⃣ The Elements of Statistical Learning book
Investigating the mathematics of ML algorithms and statistical learning methods.
Link: PDF


9️⃣ DATA SMART book
Implementing complex data science problems using Excel and the tips and tricks of this process.
Link: PDF


πŸ”Ÿ Intro to Statistical Learning with Python book
Examples and practical applications of Python language in data science projects.
Link: PDF

#TechVibe #TechResources @alnova19
"Where you're born isn't your ceiling" we can make it peps✌️

#TechVibe @alnova19
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Chapa and telebirr requires a business license, in test env, they don need. but when you on production with real payment, you required to provide the license of business certificate and agreement

#TechVibe #Chapa #TeleBirr @alnova19
am not even a react dev but recently somebody told me about KIRO(AI IDE by Amazon) and tried by building cluelessdev.vercel.app this in just 40 min.