𝗧𝗖𝗦 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍

Want to kickstart your career in Data Analytics but don’t know where to begin?👨‍💻

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Just pure, job-ready learning📍

Here are 8 concise tips to help you ace a technical AI engineering interview:

𝟭. 𝗘𝘅𝗽𝗹𝗮𝗶𝗻 𝗟𝗟𝗠 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 - Cover the high-level workings of models like GPT-3, including transformers, pre-training, fine-tuning, etc.

𝟮. 𝗗𝗶𝘀𝗰𝘂𝘀𝘀 𝗽𝗿𝗼𝗺𝗽𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 - Talk through techniques like demonstrations, examples, and plain language prompts to optimize model performance.

𝟯. 𝗦𝗵𝗮𝗿𝗲 𝗟𝗟𝗠 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗲𝘅𝗮𝗺𝗽𝗹𝗲𝘀 - Walk through hands-on experiences leveraging models like GPT-4, Langchain, or Vector Databases.

𝟰. 𝗦𝘁𝗮𝘆 𝘂𝗽𝗱𝗮𝘁𝗲𝗱 𝗼𝗻 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 - Mention latest papers and innovations in few-shot learning, prompt tuning, chain of thought prompting, etc.

𝟱. 𝗗𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝗺𝗼𝗱𝗲𝗹 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 - Compare transformer networks like GPT-3 vs Codex. Explain self-attention, encodings, model depth, etc.

𝟲. 𝗗𝗶𝘀𝗰𝘂𝘀𝘀 𝗳𝗶𝗻𝗲-𝘁𝘂𝗻𝗶𝗻𝗴 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 - Explain supervised fine-tuning, parameter efficient fine tuning, few-shot learning, and other methods to specialize pre-trained models for specific tasks.

𝟳. 𝗗𝗲𝗺𝗼𝗻𝘀𝘁𝗿𝗮𝘁𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 - From tokenization to embeddings to deployment, showcase your ability to operationalize models at scale.

𝟴. 𝗔𝘀𝗸 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝗳𝘂𝗹 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 - Inquire about model safety, bias, transparency, generalization, etc. to show strategic thinking.

Free AI Resources: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y

𝟲 𝗕𝗲𝘀𝘁 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹𝘀 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜😍

Power BI Isn’t Just a Tool—It’s a Career Game-Changer🚀

Whether you’re a student, a working professional, or switching careers, learning Power BI can set you apart in the competitive world of data analytics📊

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Your Analytics Journey Starts Now✅️

Inside Generative AI
Rick Spair, 2024

LLM Cheatsheet

Introduction to LLMs
- LLMs (Large Language Models) are AI systems that generate text by predicting the next word.
- Prompts are the instructions or text you give to an LLM.
- Personas allow LLMs to take on specific roles or tones.
- Learning types:
- Zero-shot (no examples given)
- One-shot (one example)
- Few-shot (a few examples)

Transformers
- The core architecture behind LLMs, using self-attention to process input sequences.
- Encoder: Understands input.
- Decoder: Generates output.
- Embeddings: Converts words into vectors.

Types of LLMs
- Encoder-only: Great for understanding (like BERT).
- Decoder-only: Best for generating text (like GPT).
- Encoder-decoder: Useful for tasks like translation and summarization (like T5).

Configuration Settings
- Decoding strategies:
- Greedy: Always picks the most likely next word.
- Beam search: Considers multiple possible sequences.
- Random sampling: Adds creativity by picking among top choices.
- Temperature: Controls randomness (higher value = more creative output).
- Top-k and Top-p: Restrict choices to the most likely words.

LLM Instruction Fine-Tuning & Evaluation
- Instruction fine-tuning: Trains LLMs to follow specific instructions.
- Task-specific fine-tuning: Focuses on a single task.
- Multi-task fine-tuning: Trains on multiple tasks for broader skills.

Model Evaluation
- Evaluating LLMs is hard-metrics like BLEU and ROUGE are common, but human judgment is often needed.

Join our WhatsApp Channel: https://whatsapp.com/channel/0029VazaRBY2UPBNj1aCrN0U

𝟱 𝗙𝗥𝗘𝗘 𝗜𝗕𝗠 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝗸𝘆𝗿𝗼𝗰𝗸𝗲𝘁 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲😍

From mastering Cloud Computing to diving into Deep Learning, Docker, Big Data, and IoT Blockchain

IBM, one of the biggest tech companies, is offering 5 FREE courses that can seriously upgrade your resume and skills — without costing you anything.

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How to start learning Generative AI

Python Libraries for Generative AI

𝟰 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗯𝘆 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗔𝗜😍

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Here’s your golden ticket to the future!✅

Perfect 😂

Guys, Big Announcement!

We’ve officially crossed 4 Lakh followers on this journey together — and it’s time to step up now! ❤️

I’m launching a Coding Interview Prep Series — designed for everyone from beginners to those polishing their skills for FAANG-level interviews.

This will be a structured, step-by-step journey — with short explanations, real coding examples, and mini-challenges after every topic to build real muscle memory.

Here’s what’s coming in the next few weeks:

Week 1: The Very Basics

- What is an Algorithm?

- What is Data Structure?

- Understanding Time Complexity (Big O Notation - made simple!)

- Basic Math for Coding Interviews

- Problem Solving Approach (How to break down a question)


Week 2: Arrays & Strings — Your Building Blocks

- Introduction to Arrays and Strings

- Common Operations (Insert, Delete, Search)

- Two Pointer Techniques (Easy to Medium problems)

- Sliding Window Problems (Optimization techniques)

- String Manipulation Tricks for Interviews


Week 3: Hashing & Recursion

- HashMaps and HashSets (Power tools for coders!)

- Solving Problems using Hashing

- Introduction to Recursion

- Base Case and Recursive Case (Explained like a 5-year-old)

- Classic Recursion Problems


Week 4: Linked Lists, Stacks & Queues

- Singly vs Doubly Linked List

- Stack Operations and Problems (Valid Parentheses, Min Stack)

- Queue and Deque Concepts (with real examples)

- When to Use Stack vs Queue in Interviews


Week 5: Trees & Graphs Essentials

- Binary Trees and BST Basics

- Tree Traversals (Inorder, Preorder, Postorder)

- Graph Representations (Adjacency List, Matrix)

- Breadth-First Search (BFS) and Depth-First Search (DFS) explained simply


Week 6: Sorting, Searching & Interview Patterns

- Core Sorting Algorithms (Selection, Bubble, Insertion)

- Advanced Sorting (Merge Sort, Quick Sort)

- Binary Search Patterns (Find First, Last Occurrence, etc.)

- Mastering Interview Patterns (Two Sum, Three Sum, Subarray Sum, etc.)


Week 7: Dynamic Programming & Advanced Problem Solving

- What is Dynamic Programming (DP)?

- Top-Down vs Bottom-Up Approach

- Memoization and Tabulation Explained

- Classic DP Problems (Fibonacci, 0/1 Knapsack, Longest Subsequence)


Week 8: Real-World Mock Interviews

- Solving Medium to Hard Problems

- Tackling FAANG-level Interview Questions

- Tips to Handle Pressure in Coding Rounds

- Building the Right Mindset for Success


React with ❤️ if you're ready for this new coding series


You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X

𝗙𝗥𝗘𝗘 𝗚𝗼𝗼𝗴𝗹𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗮𝘁𝗵! 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱😍

If you’re dreaming of starting a high-paying data career or switching into the booming tech industry, Google just made it a whole lot easier — and it’s completely FREE👨‍💻

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You can use ChatGPT to make money online.

Here are 10 prompts by ChatGPT

1. Develop Email Newsletters:

Make interesting email newsletters to keep audience updated and engaged.

Prompt: "I run a local community news website. Can you help me create a weekly email newsletter that highlights key local events, stories, and updates in a compelling way?"

2. Create Online Course Material:

Make detailed and educational online course content.

Prompt: "I'm creating an online course about basic programming for beginners. Can you help me generate a syllabus and detailed lesson plans that cover fundamental concepts in an easy-to-understand manner?"

Read more......

List of AI Project Ideas 👨🏻‍💻🤖 -

Beginner Projects

🔹 Sentiment Analyzer
🔹 Image Classifier
🔹 Spam Detection System
🔹 Face Detection
🔹 Chatbot (Rule-based)
🔹 Movie Recommendation System
🔹 Handwritten Digit Recognition
🔹 Speech-to-Text Converter
🔹 AI-Powered Calculator
🔹 AI Hangman Game

Intermediate Projects

🔸 AI Virtual Assistant
🔸 Fake News Detector
🔸 Music Genre Classification
🔸 AI Resume Screener
🔸 Style Transfer App
🔸 Real-Time Object Detection
🔸 Chatbot with Memory
🔸 Autocorrect Tool
🔸 Face Recognition Attendance System
🔸 AI Sudoku Solver

Advanced Projects

🔺 AI Stock Predictor
🔺 AI Writer (GPT-based)
🔺 AI-powered Resume Builder
🔺 Deepfake Generator
🔺 AI Lawyer Assistant
🔺 AI-Powered Medical Diagnosis
🔺 AI-based Game Bot
🔺 Custom Voice Cloning
🔺 Multi-modal AI App
🔺 AI Research Paper Summarizer

Join for more: https://t.me/machinelearning_deeplearning

𝗕𝗲𝘀𝘁 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗦𝗸𝗶𝗹𝗹𝘀 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘😍

Dreaming of becoming a Data Analyst but feel overwhelmed by where to start?👨‍💻

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