1.2M
CHMachine learning relies heavily on mathematical foundations.
#tech #ml #explore #fyp #ai
@chrisoh.zip
#Colab Machine Learning
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455.4K
CHHere’s your full roadmap on how to get into machine learning. Comment “Roadmap” to get the pdf.
Save and follow for more.
#ai #machinelearning #coding #programming #cs
@chrispathway
1.1K
TEWant to start coding instantly with Google Colab? 🚀💻
This quick guide shows how to use Google Colab to run Python code online—no installation, no setup, completely free.
Just open Colab, create a new notebook, and start coding with built-in libraries, GPU support, and easy file uploads.
Perfect for beginners, students, data learners, or anyone stuck with a low-spec PC but big coding goals.
💾 Save, Share, Comment, Follow @techshan_404 for more daily coding tools, tech tips & productivity hacks! 🔥
#googlecolab #python #machinelearning #computertips #learntech
@techshan_404
2.1K
AI🚀 *No GPU? No problem.*
You can now train and fine-tune LLMs directly from VS Code using a *free Google Colab runtime* 🤯
This workflow lets you:
→ Connect your fine-tuning notebooks to Colab
→ Train locally or on a free cloud GPU
→ Use tools like *Unsloth* to speed up training
For builders, students, and startup teams working on AI products (like many of us experimenting with AI-driven tools, EDA automation, or ML pipelines 🚀), this removes one of the biggest barriers—*hardware access.*
Huge credit to *@dr_cintas* for sharing this awesome guide 👏
👉 Guide Link: https://t.co/W27h3ciVhh
Follow @dr_cintas for more.
If you want more practical AI gems and real-world use cases, join the free newsletter with daily tutorials and latest AI news:
👉 http://simplifyingai.co
💡 Whether you're building LLM features, experimenting with AI copilots, or exploring new workflows for your next startup idea, tools like this can dramatically speed up learning and prototyping.
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#AI #ArtificialIntelligence #MachineLearning #LLM #DeepLearning #AItools #TechReels #StartupLife #Developers #Coding #Python #VSCode #GoogleColab #OpenSource #FutureOfWork #Innovation #TechInnovation #BuildInPublic #LearnAI #AICommunity #AIRevolution #Automation #TechNews #ViralTech
@aiproductlabs
1.8M
MADo you think we can build a solid model at the end of this year? #formula1 #machinelearning #programming
@mar_antaya
89.4K
VOComment “ML” and I’ll send you the links.
You don’t need overpriced AI courses to break into machine learning. Some of the best ML and LLM resources are free, open-source, and built by top engineers and researchers.
📌 5 High-Impact GitHub Repos to Master Machine Learning & AI:
1️⃣ ML-For-Beginners
A structured, beginner-friendly roadmap covering machine learning fundamentals like regression, classification, clustering, and model evaluation. Perfect if you want a guided introduction to ML without jumping between random tutorials.
2️⃣ bitsandbytes
Learn 8-bit and 4-bit quantization for large language models. Essential if you want to run or fine-tune LLMs efficiently on limited GPU memory using techniques like QLoRA and low-bit training.
3️⃣ LLMs-from-scratch
Build large language models step by step to truly understand transformers, attention mechanisms, tokenization, and training loops. Ideal for developers who want to understand how GPT-style models actually work under the hood.
4️⃣ LangChain
A framework for building AI agents, RAG pipelines, and LLM-powered applications. Connect models to tools, vector databases, APIs, and real-time data sources to create production-ready AI systems.
5️⃣ LoRA (Low-Rank Adaptation)
A powerful method for parameter-efficient fine-tuning. Train massive models by updating only a small fraction of weights — reducing cost while keeping performance strong.
These repos cover core AI skills like deep learning, transformers, quantization, LLM fine-tuning, retrieval-augmented generation (RAG), AI agents, and efficient model deployment.
Whether you're preparing for an ML engineer role, building AI startups, experimenting with open-source LLMs, or leveling up your deep learning knowledge, these resources will dramatically accelerate your progress.
Save this, share it, and start building real AI skills the smart way.
@volkan.js
410
SICorso gratuito su come Quantizzare un modello di machine learning!
Prima cosa in questo video spiego cos'è la quantizzazione a cosa serve e teoricamente cosa implica. Successivamente andremo in un google colab notebook a fare degli esempi hands on quantizzando un large language model open source.
#llm #chatgpt #ai #ia #intelligenzaartificiale #quantization
@simorizzo_ai
1.4K
WI💻 Google Colab: A Game-Changer for Students & Professionals
For anyone starting with Python, Data Science, or Machine Learning, Google Colab is one of the most powerful (and free) tools available. 🚀
✅ Run Python code directly in your browser
✅ No installation or setup required
✅ Access to GPUs for faster model training
✅ Perfect for collaboration on projects & research
We introduce our students to tools like Google Colab so they gain hands-on experience with the same platforms used in the industry.
👉 Have you tried Google Colab yet? Share your experience in the comments!
#GoogleColab #DataScience #MachineLearning #ArtificialIntelligence #PythonCoding #FutureSkills #CareerGrowth #PlacementReady #StudentOpportunities
@wininlifeacademy
1.3M
SAI’ve been asked many times where to start learning ML, so after talking to so many experts in this field, this is a good place to start.
Comment down below “TRAIN” and I’ll send you a more in-depth checklist along with the best GitHub links to help you start learning each concept.
If you don’t receive the link you either need to follow first then comment, or your instagram is outdated. Either way, no worries. send me a dm and I’ll get it to you ASAP.
#cs #ai #dev #university #softwareengineer #viral #advice #machinelearning
@sambhav_athreya
18.0K
AAMachine Learning Projects with implementation 👨💻💡
Get access to 150+ machine learning projects with step-by-step guides for all skill levels. Whether you’re a beginner or an expert, these projects cover everything from predictive analytics and image classification to sentiment analysis and anomaly detection.
Each project includes:
• Practical Implementation: Real-world applications with easy-to-follow code.
• Customizable Ideas: Modify projects to fit your learning goals.
• Diverse Domains: NLP, computer vision, recommendation systems, and more.
Comment Projects and I’ll share the link directly! Start building and leveling up your ML skills now!
[Machine Learning, ML Projects, Deep Learning, Data Science, AI Projects, Data Science Projects, Python , Data Analytics]
#MachineLearning #MLProjects #DataScience #AIProjects #DeepLearning #DataScienceProjects #ArtificialIntelligence #MachineLearningProjects #AI #TechSkills #LearnAI #projects #hiring #aasifcodes #jobs
@aasifcodes
156.4K
TEYou can now train LLMs in VS code for FREE via Colab & Unsloth AI. They made a guide to connect any fine-tuning notebook in VS Code to a Google Colab runtime.
You can train locally or on a free Google Colab GPU.
VS Code guide: https://unsloth.ai/docs/get-started/install/vs-code
Github Repo: https://github.com/unslothai/unsloth
🎬 Unsloth AI
@techwith.ram
13.0K
CODay 3 of Day 15 Fundamental NLP😉
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I combined my day 1 and day 2 of NLP learning into one Google Colab project, which I have learned about different methods of tokenisation, stemming and lemmatisation.
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Day 3 is about sentiment analysis using transformer models, but I’m trying to learn about TF-IDF as well and trying to build my own sentiment analysis model. Day 3 is going to be 2 days I guess 😅
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More to come! I’m working on my startup but still being able to learn and progress everyday day, which is enough 😎
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I’m a self taught software engineer turned startup founder, trying to learn machine learning and deep learning 🤓
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Follow my journey!
.
All the best for you 😎
.
For partnership, please email codershearycoding@gmail.com
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#coding #artificialintelligence #ai #machinelearning #ml #productivity #motivation #python #learntocode #coding #code #tech #technology #startup #startuplife #entrepreneur #entrepreneurship #reelsinstagram #reels #study #studygram #futuretechnology #coursetosuccess
@codersheary
✨ #Colab Machine Learning Discovery Guide
Instagram hosts thousands of posts under #Colab Machine Learning, creating one of the platform's most vibrant visual ecosystems. This massive collection represents trending moments, creative expressions, and global conversations happening right now.
The massive #Colab Machine Learning collection on Instagram features today's most engaging videos. Content from @mar_antaya, @sambhav_athreya and @chrisoh.zip and other creative producers has reached thousands of posts globally. Filter and watch the freshest #Colab Machine Learning reels instantly.
What's trending in #Colab Machine Learning? The most watched Reels videos and viral content are featured above. Explore the gallery to discover creative storytelling, popular moments, and content that's capturing millions of views worldwide.
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📹 Video Trends: Discover the latest Reels and viral videos
📈 Hashtag Strategy: Explore trending hashtag options for your content
🌟 Featured Creators: @mar_antaya, @sambhav_athreya, @chrisoh.zip and others leading the community
FAQs About #Colab Machine Learning
With Pictame, you can browse all #Colab Machine Learning reels and videos without logging into Instagram. No account required and your activity remains private.
Content Performance Insights
Analysis of 12 reels
💡 Top performing posts average 1.2M views (2.8x above average). High competition - quality and timing are critical.
Focus on peak engagement hours (typically 11 AM-1 PM, 7-9 PM) and trending formats
Content Creation Tips & Strategy
💡 Top performing content gets over 10K views - focus on engaging first 3 seconds
✨ Many verified creators are active (42%) - study their content style for inspiration
📹 High-quality vertical videos (9:16) perform best for #Colab Machine Learning - use good lighting and clear audio
✍️ Detailed captions with story work well - average caption length is 675 characters
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Explore Colab Machine Learning#learning#learn#machine learning#colab#learned#colabs#colabe#learn machine learning