If you don't know where to download AI models for your application, then they are easy to download from here.
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
```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
β€2
Coding is tricky. Coding in interviews feels even harder. Itβs 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
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
Forwarded from YearProgressET
ββββββββββββββββ α©% (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 youβve wanted to build environments but lacked compute or support - this is for you
@DagmawiBabiJobs
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 youβve wanted to build environments but lacked compute or support - this is for you
@DagmawiBabiJobs
TechVibe
A friend of mine sent me this, and I really think we should spend some serious time with our friend talking about real-life issues. What do you think? #TechVibe #RealConversations #Meet-ups @alnova19
Media is too big
VIEW IN TELEGRAM
By the way, this is how we celebrated with my highschool batch yesterday it was crazy frπ
#TechVibe #Friends @alnova19
#TechVibe #Friends @alnova19
β€6
Forwarded from α₯α±α£αα
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 overloadedβalong with the official Telegram botβwhen hit by a massive number of students all at once.
#esubalew #grade12
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 overloadedβalong with the official Telegram botβwhen hit by a massive number of students all at once.
#esubalew #grade12
β€3
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 theyβve 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 donβt 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 canβt even imagine it.
For me, this is one of the biggest problems in Ethiopia, because I move fast and donβt like wasting time.
#TechVibe @alnova19
I honestly donβt 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 canβt even imagine it.
For me, this is one of the biggest problems in Ethiopia, because I move fast and donβt like wasting time.
#TechVibe @alnova19
π1
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. π
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
Nobody looks at a caterpillar and judges it for not being a butterfly yet. We understand it's in a state of progress. π
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 π
|
|ββ Variables
| βββ var
| βββ let
| βββ const
|
|ββ Data Types
| βββ String
| βββ Number
| βββ Boolean
| βββ Object
| βββ Array
| βββ Null
| βββ Undefined
|
|ββ Operators
| βββ Arithmetic
| βββ Assignment
| βββ Comparison
| βββ Logical
| βββ Unary
| βββ Ternary (Conditional)
||ββ Control Flow
| βββ if statement
| βββ else statement
| βββ else if statement
| βββ switch statement
| βββ for loop
| βββ while loop
| βββ do-while loop
|
|ββ Functions
| βββ Function declaration
| βββ Function expression
| βββ Arrow function
| βββ IIFE (Immediately Invoked Function Expression)
|
|ββ Scope
| βββ Global scope
| βββ Local scope
| βββ Block scope
| βββ Lexical scope
||ββ Arrays
| βββ Array methods
| | βββ push()
| | βββ pop()
| | βββ shift()
| | βββ unshift()
| | βββ splice()
| | βββ slice()
| | βββ concat()
| βββ Array iteration
| βββ forEach()
| βββ map()
| βββ filter()
| βββ reduce()|
|ββ Objects
| βββ Object properties
| | βββ Dot notation
| | βββ Bracket notation
| βββ Object methods
| | βββ Object.keys()
| | βββ Object.values()
| | βββ Object.entries()
| βββ Object destructuring
||ββ Promises
| βββ Promise states
| | βββ Pending
| | βββ Fulfilled
| | βββ Rejected
| βββ Promise methods
| | βββ then()
| | βββ catch()
| | βββ finally()
| βββ Promise.all()
|
|ββ Asynchronous JavaScript
| βββ Callbacks
| βββ Promises
| βββ Async/Await
|
|ββ Error Handling
| βββ try...catch statement
| βββ throw statement
|
|ββ JSON (JavaScript Object Notation)
||ββ Modules
| βββ import
| βββ export
|
|ββ DOM Manipulation
| βββ Selecting elements
| βββ Modifying elements
| βββ Creating elements
|
|ββ Events
| βββ Event listeners
| βββ Event propagation
| βββ Event delegation
|
|ββ AJAX (Asynchronous JavaScript and XML)
|
|ββ Fetch API
||ββ ES6+ Features
| βββ Template literals
| βββ Destructuring assignment
| βββ Spread/rest operator
| βββ Arrow functions
| βββ Classes
| βββ let and const
| βββ Default parameters
| βββ Modules
| βββ Promises
|
|ββ Web APIs
| βββ Local Storage
| βββ Session Storage
| βββ Web Storage API
|
|ββ Libraries and Frameworks
| βββ React
| βββ Angular
| βββ Vue.js
||ββ Debugging
| βββ Console.log()
| βββ Breakpoints
| βββ DevTools
|
|ββ Others
| βββ Closures
| βββ Callbacks
| βββ Prototypes
| βββ this keyword
| βββ Hoisting
| βββ Strict mode
|
| END __
#TechVibe #JavaScript @alnova19
The JavaScript Tree π
|
|ββ Variables
| βββ var
| βββ let
| βββ const
|
|ββ Data Types
| βββ String
| βββ Number
| βββ Boolean
| βββ Object
| βββ Array
| βββ Null
| βββ Undefined
|
|ββ Operators
| βββ Arithmetic
| βββ Assignment
| βββ Comparison
| βββ Logical
| βββ Unary
| βββ Ternary (Conditional)
||ββ Control Flow
| βββ if statement
| βββ else statement
| βββ else if statement
| βββ switch statement
| βββ for loop
| βββ while loop
| βββ do-while loop
|
|ββ Functions
| βββ Function declaration
| βββ Function expression
| βββ Arrow function
| βββ IIFE (Immediately Invoked Function Expression)
|
|ββ Scope
| βββ Global scope
| βββ Local scope
| βββ Block scope
| βββ Lexical scope
||ββ Arrays
| βββ Array methods
| | βββ push()
| | βββ pop()
| | βββ shift()
| | βββ unshift()
| | βββ splice()
| | βββ slice()
| | βββ concat()
| βββ Array iteration
| βββ forEach()
| βββ map()
| βββ filter()
| βββ reduce()|
|ββ Objects
| βββ Object properties
| | βββ Dot notation
| | βββ Bracket notation
| βββ Object methods
| | βββ Object.keys()
| | βββ Object.values()
| | βββ Object.entries()
| βββ Object destructuring
||ββ Promises
| βββ Promise states
| | βββ Pending
| | βββ Fulfilled
| | βββ Rejected
| βββ Promise methods
| | βββ then()
| | βββ catch()
| | βββ finally()
| βββ Promise.all()
|
|ββ Asynchronous JavaScript
| βββ Callbacks
| βββ Promises
| βββ Async/Await
|
|ββ Error Handling
| βββ try...catch statement
| βββ throw statement
|
|ββ JSON (JavaScript Object Notation)
||ββ Modules
| βββ import
| βββ export
|
|ββ DOM Manipulation
| βββ Selecting elements
| βββ Modifying elements
| βββ Creating elements
|
|ββ Events
| βββ Event listeners
| βββ Event propagation
| βββ Event delegation
|
|ββ AJAX (Asynchronous JavaScript and XML)
|
|ββ Fetch API
||ββ ES6+ Features
| βββ Template literals
| βββ Destructuring assignment
| βββ Spread/rest operator
| βββ Arrow functions
| βββ Classes
| βββ let and const
| βββ Default parameters
| βββ Modules
| βββ Promises
|
|ββ Web APIs
| βββ Local Storage
| βββ Session Storage
| βββ Web Storage API
|
|ββ Libraries and Frameworks
| βββ React
| βββ Angular
| βββ Vue.js
||ββ Debugging
| βββ Console.log()
| βββ Breakpoints
| βββ DevTools
|
|ββ Others
| βββ Closures
| βββ Callbacks
| βββ Prototypes
| βββ this keyword
| βββ Hoisting
| βββ Strict mode
|
| END __
#TechVibe #JavaScript @alnova19
π2
π 10 of the best free books in the field of data science
π that you should include in your learning program!
1οΈβ£ Python Data Science Handbook
Using unique Python libraries with a focus on data science.
Link: PDF
2οΈβ£ 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
3οΈβ£ Deep Learning book
The best book for machine learning and deep learning written by 3 active and top researchers in these fields.
Link: PDF
4οΈβ£ R for Data Science book
This book reflects the best ways to use R in data science.
Link: PDF
5οΈβ£ 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
6οΈβ£ Machine Learning Yearning book
Error detection in machine learning projects.
Link: PDF
7οΈβ£ Bayesian Methods for Hackers book
Practical applications of Bayesian inference and probabilistic programming.
Link: PDF
8οΈβ£ The Elements of Statistical Learning book
Investigating the mathematics of ML algorithms and statistical learning methods.
Link: PDF
9οΈβ£ DATA SMART book
Implementing complex data science problems using Excel and the tips and tricks of this process.
Link: PDF
π Intro to Statistical Learning with Python book
Examples and practical applications of Python language in data science projects.
Link: PDF
#TechVibe #TechResources @alnova19
π that you should include in your learning program!
1οΈβ£ Python Data Science Handbook
Using unique Python libraries with a focus on data science.
Link: PDF
2οΈβ£ 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
3οΈβ£ Deep Learning book
The best book for machine learning and deep learning written by 3 active and top researchers in these fields.
Link: PDF
4οΈβ£ R for Data Science book
This book reflects the best ways to use R in data science.
Link: PDF
5οΈβ£ 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
6οΈβ£ Machine Learning Yearning book
Error detection in machine learning projects.
Link: PDF
7οΈβ£ Bayesian Methods for Hackers book
Practical applications of Bayesian inference and probabilistic programming.
Link: PDF
8οΈβ£ The Elements of Statistical Learning book
Investigating the mathematics of ML algorithms and statistical learning methods.
Link: PDF
9οΈβ£ DATA SMART book
Implementing complex data science problems using Excel and the tips and tricks of this process.
Link: PDF
π Intro to Statistical Learning with Python book
Examples and practical applications of Python language in data science projects.
Link: PDF
#TechVibe #TechResources @alnova19
Forwarded from Ros's perspective π§βπ»π€
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.