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Create pivot tables in your Jupyter Notebook:
Here's the link to the #GitHub repo and documentation:
https://pivottable.js.org/examples/
Here's the link to the #GitHub repo and documentation:
https://pivottable.js.org/examples/
#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras
https://t.iss.one/DataScienceM
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Forwarded from Machine Learning with Python
A Complete Course to Learn Robotics and Perception
Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson
github.com/gtbook/robotics
roboticsbook.org/intro.html
⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson
github.com/gtbook/robotics
roboticsbook.org/intro.html
#Robotics #Perception #AI #DeepLearning #ComputerVision #RoboticsCourse #MachineLearning #Education #RoboticsResearch #GitHub
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Microsoft launched the best course on Generative AI!
The Free 21 lesson course is available on #Github and will teach you everything you need to know to start building #GenerativeAI applications.
Enroll: https://github.com/microsoft/generative-ai-for-beginners
https://github.com/microsoft/generative-ai-for-beginners🩷
The Free 21 lesson course is available on #Github and will teach you everything you need to know to start building #GenerativeAI applications.
Enroll: https://github.com/microsoft/generative-ai-for-beginners
https://github.com/microsoft/generative-ai-for-beginners
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🔥 Trending Repository: dyad
📝 Description: Free, local, open-source AI app builder ✨ v0 / lovable / Bolt alternative 🌟 Star if you like it!
🔗 Repository URL: https://github.com/dyad-sh/dyad
🌐 Website: https://dyad.sh
📖 Readme: https://github.com/dyad-sh/dyad#readme
📊 Statistics:
🌟 Stars: 13.2K stars
👀 Watchers: 73
🍴 Forks: 1.3K forks
💻 Programming Languages: TypeScript - JavaScript - CSS - HTML - Shell - Python
🏷️ Related Topics:
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: Free, local, open-source AI app builder ✨ v0 / lovable / Bolt alternative 🌟 Star if you like it!
🔗 Repository URL: https://github.com/dyad-sh/dyad
🌐 Website: https://dyad.sh
📖 Readme: https://github.com/dyad-sh/dyad#readme
📊 Statistics:
🌟 Stars: 13.2K stars
👀 Watchers: 73
🍴 Forks: 1.3K forks
💻 Programming Languages: TypeScript - JavaScript - CSS - HTML - Shell - Python
🏷️ Related Topics:
#github #react #typescript #nextjs #artificial_intelligence #gemini #openai #bolt #v0 #lovable #vercel #llm #llms #generative_ai #anthropic #ollama #qwen #deepseek #ai_app_builder
==================================
🧠 By: https://t.iss.one/DataScienceM
🤖🧠 AI Projects : A Comprehensive Showcase of Machine Learning, Deep Learning and Generative AI
🗓️ 27 Oct 2025
📚 AI News & Trends
Artificial Intelligence (AI) is transforming industries across the globe, driving innovation through automation, data-driven insights and intelligent decision-making. Whether it’s predicting house prices, detecting diseases or building conversational chatbots, AI is at the core of modern digital solutions. The AI Project Gallery by Hema Kalyan Murapaka is an exceptional GitHub repository that curates a wide ...
#AI #MachineLearning #DeepLearning #GenerativeAI #ArtificialIntelligence #GitHub
🗓️ 27 Oct 2025
📚 AI News & Trends
Artificial Intelligence (AI) is transforming industries across the globe, driving innovation through automation, data-driven insights and intelligent decision-making. Whether it’s predicting house prices, detecting diseases or building conversational chatbots, AI is at the core of modern digital solutions. The AI Project Gallery by Hema Kalyan Murapaka is an exceptional GitHub repository that curates a wide ...
#AI #MachineLearning #DeepLearning #GenerativeAI #ArtificialIntelligence #GitHub
Forwarded from Machine Learning with Python
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YOLO Training Template
Manual data labeling has become significantly more convenient. Now the process looks like in the usual labeling systems - you just outline the object with a frame and a bounding box is immediately created.
The platform allows:
• to upload your own dataset
• to label manually or auto-label via DINOv3
• to enrich the data if desired
• to train a #YOLO model on your own data
• to run inference immediately
• to export to ONNX or NCNN, which ensures compatibility with edge hardware and smartphones
All of this is available for free and can already be tested on #GitHub.
Repo:
https://github.com/computer-vision-with-marco/yolo-training-template
https://t.iss.one/CodeProgrammer
Manual data labeling has become significantly more convenient. Now the process looks like in the usual labeling systems - you just outline the object with a frame and a bounding box is immediately created.
The platform allows:
• to upload your own dataset
• to label manually or auto-label via DINOv3
• to enrich the data if desired
• to train a #YOLO model on your own data
• to run inference immediately
• to export to ONNX or NCNN, which ensures compatibility with edge hardware and smartphones
All of this is available for free and can already be tested on #GitHub.
Repo:
https://github.com/computer-vision-with-marco/yolo-training-template
https://t.iss.one/CodeProgrammer
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