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
❤2
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
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 Dagmawi Babi Jobs
Join the Prime Intellect RL Residency
Apply here
• form.typeform.com/to/ibQawo5e
The RL Residency gives you:
• Compute for experiments
• A stipend
• Hands-on support from our internal research team
Who should apply?
• Grad students with research ideas
• Independent builders & hackers
• 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
Apply here
• form.typeform.com/to/ibQawo5e
The RL Residency gives you:
• Compute for experiments
• A stipend
• Hands-on support from our internal research team
Who should apply?
• Grad students with research ideas
• Independent builders & hackers
• 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
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 fr😊
#TechVibe #Friends @alnova19
#TechVibe #Friends @alnova19
❤6
Forwarded from እሱባለው
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 overloaded—along with the official Telegram bot—when 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 overloaded—along with the official Telegram bot—when hit by a massive number of students all at once.
#esubalew #grade12
❤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 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
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
👍1
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. 🐛
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. 🐛
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 Javanoscript :
The JavaScript Tree 👇
|
|── Variables
| ├── var
| ├── let
| └── const
|
|── Data Types
| ├── String
| ├── Number
| ├── Boolean
| ├── Object
| ├── Array
| ├── Null
| └── Undefined
|
|── Operators
| ├── Arithmetic
| ├── Assignment
| ├── Comparison
| ├── Logical
| ├── Unary
| └── Ternary (Conditional)
||── Control Flow
| ├── if statement
| ├── else statement
| ├── else if statement
| ├── switch statement
| ├── for loop
| ├── while loop
| └── do-while loop
|
|── Functions
| ├── Function declaration
| ├── Function expression
| ├── Arrow function
| └── IIFE (Immediately Invoked Function Expression)
|
|── Scope
| ├── Global scope
| ├── Local scope
| ├── Block scope
| └── Lexical scope
||── Arrays
| ├── Array methods
| | ├── push()
| | ├── pop()
| | ├── shift()
| | ├── unshift()
| | ├── splice()
| | ├── slice()
| | └── concat()
| └── Array iteration
| ├── forEach()
| ├── map()
| ├── filter()
| └── reduce()|
|── Objects
| ├── Object properties
| | ├── Dot notation
| | └── Bracket notation
| ├── Object methods
| | ├── Object.keys()
| | ├── Object.values()
| | └── Object.entries()
| └── Object destructuring
||── Promises
| ├── Promise states
| | ├── Pending
| | ├── Fulfilled
| | └── Rejected
| ├── Promise methods
| | ├── then()
| | ├── catch()
| | └── finally()
| └── Promise.all()
|
|── Asynchronous JavaScript
| ├── Callbacks
| ├── Promises
| └── Async/Await
|
|── Error Handling
| ├── try...catch statement
| └── throw statement
|
|── JSON (JavaScript Object Notation)
||── Modules
| ├── import
| └── export
|
|── DOM Manipulation
| ├── Selecting elements
| ├── Modifying elements
| └── Creating elements
|
|── Events
| ├── Event listeners
| ├── Event propagation
| └── Event delegation
|
|── AJAX (Asynchronous JavaScript and XML)
|
|── Fetch API
||── ES6+ Features
| ├── Template literals
| ├── Destructuring assignment
| ├── Spread/rest operator
| ├── Arrow functions
| ├── Classes
| ├── let and const
| ├── Default parameters
| ├── Modules
| └── Promises
|
|── Web APIs
| ├── Local Storage
| ├── Session Storage
| └── Web Storage API
|
|── Libraries and Frameworks
| ├── React
| ├── Angular
| └── Vue.js
||── Debugging
| ├── Console.log()
| ├── Breakpoints
| └── DevTools
|
|── Others
| ├── Closures
| ├── Callbacks
| ├── Prototypes
| ├── this keyword
| ├── Hoisting
| └── Strict mode
|
| END __
#TechVibe #JavaScript @alnova19
The JavaScript Tree 👇
|
|── Variables
| ├── var
| ├── let
| └── const
|
|── Data Types
| ├── String
| ├── Number
| ├── Boolean
| ├── Object
| ├── Array
| ├── Null
| └── Undefined
|
|── Operators
| ├── Arithmetic
| ├── Assignment
| ├── Comparison
| ├── Logical
| ├── Unary
| └── Ternary (Conditional)
||── Control Flow
| ├── if statement
| ├── else statement
| ├── else if statement
| ├── switch statement
| ├── for loop
| ├── while loop
| └── do-while loop
|
|── Functions
| ├── Function declaration
| ├── Function expression
| ├── Arrow function
| └── IIFE (Immediately Invoked Function Expression)
|
|── Scope
| ├── Global scope
| ├── Local scope
| ├── Block scope
| └── Lexical scope
||── Arrays
| ├── Array methods
| | ├── push()
| | ├── pop()
| | ├── shift()
| | ├── unshift()
| | ├── splice()
| | ├── slice()
| | └── concat()
| └── Array iteration
| ├── forEach()
| ├── map()
| ├── filter()
| └── reduce()|
|── Objects
| ├── Object properties
| | ├── Dot notation
| | └── Bracket notation
| ├── Object methods
| | ├── Object.keys()
| | ├── Object.values()
| | └── Object.entries()
| └── Object destructuring
||── Promises
| ├── Promise states
| | ├── Pending
| | ├── Fulfilled
| | └── Rejected
| ├── Promise methods
| | ├── then()
| | ├── catch()
| | └── finally()
| └── Promise.all()
|
|── Asynchronous JavaScript
| ├── Callbacks
| ├── Promises
| └── Async/Await
|
|── Error Handling
| ├── try...catch statement
| └── throw statement
|
|── JSON (JavaScript Object Notation)
||── Modules
| ├── import
| └── export
|
|── DOM Manipulation
| ├── Selecting elements
| ├── Modifying elements
| └── Creating elements
|
|── Events
| ├── Event listeners
| ├── Event propagation
| └── Event delegation
|
|── AJAX (Asynchronous JavaScript and XML)
|
|── Fetch API
||── ES6+ Features
| ├── Template literals
| ├── Destructuring assignment
| ├── Spread/rest operator
| ├── Arrow functions
| ├── Classes
| ├── let and const
| ├── Default parameters
| ├── Modules
| └── Promises
|
|── Web APIs
| ├── Local Storage
| ├── Session Storage
| └── Web Storage API
|
|── Libraries and Frameworks
| ├── React
| ├── Angular
| └── Vue.js
||── Debugging
| ├── Console.log()
| ├── Breakpoints
| └── DevTools
|
|── Others
| ├── Closures
| ├── Callbacks
| ├── Prototypes
| ├── this keyword
| ├── Hoisting
| └── Strict mode
|
| END __
#TechVibe #JavaScript @alnova19
👍2
📚 10 of the best free books in the field of data science
📑 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
🔟 Intro to Statistical Learning with Python book
Examples and practical applications of Python language in data science projects.
Link: PDF
#TechVibe #TechResources @alnova19
📑 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
🔟 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 🧑💻🤖
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.