GitHub Education’s Post

I’m thrilled to share that I’ve completed and obtained a new certification: Supervised Machine Learning: Regression and Classification from DeepLearning.AI! 🎉 This course, taught by the amazing Andrew Ng, deepened my understanding of essential machine learning concepts such as regression, classification, model evaluation, and much more. It has been a rewarding learning journey, filled with hands-on projects and real-world applications that are sure to boost my AI skills. 🚀 To further contribute to the community, I’ve created a GitHub repository where I’ve compiled all the interactive notebooks I worked on during the course. These notebooks contain detailed implementations and code snippets that may be useful for anyone exploring machine learning concepts. 👉 Here’s the link to my repository: https://lnkd.in/eqKrmuxK Feel free to take a look, use them, and drop any feedback or suggestions! Let’s continue learning and growing together. ❤️ #MachineLearning #AI #DeepLearning #DataScience #AndrewNg #Coursera #GitHub

Just came across this little article— according to a recent Gartner study, by 2027, 80% of software engineers will need to upskill to stay relevant in an AI-driven world. It’s not just about coding, debugging, or system design anymore—it’s about understanding machine learning models, neural networks, and blending data science with software engineering. But here’s the kicker: it’s that natural curiosity, that fire to learn and adapt, that will truly drive us forward in this ever-changing world. As long as that spark is alive, staying relevant becomes a journey, not a challenge. #AI #MachineLearning #SoftwareEngineering #Upskilling

Finished. Partly ;) Today i successfully finished my first project on my learning path into AI. That was quite cool - to refresh my old coding skills, learning a new coding language and learning more from feedback in this project. One learning i want to share: Read the instructions in detail… had to do a review, because my output was not as expected. But, and that is great, the feedback was very professional, understandable and helpful! Big thanks to the reviewer!! Next step: working on my own very first image classifier. After a refresher on calculus and linear algebra as well as a deeper dive into neural networks. #udacity #AWS #AI #neverstoplearning

5 Best Github Repos to help you become a better ML / AI engineer: 1. Applied ML. All About Machine Learning in Production by Eugene Yan (26k stars) - https://lnkd.in/gwrkyJtf 2. Awesome Scalability. Build scalable ML systems by Binh Nguyen (56k stars) - https://lnkd.in/ghshNVKh 3. Creme de la Creme of Free AI courses by Piotr Skalski (4.7k stars) - https://lnkd.in/gy4cPJZ6 4. 60 Implementations of Deep Learning papers by labml.ai (60k stars) - https://lnkd.in/gnNE8Ptm 5. Made with ML. Learn to design, develop, and deploy production-grade ML applications by Goku Mohandas (36k stars) - https://lnkd.in/gjCQqjiC If you find these helpful... 👍 React ♻️ Share 💬 Comment So more people can learn. --- Happy building and experimenting!

A platform to learn and gain insights as per interest. Look into the GitHub Repositories to gain knowledge on Machine Learning and Artificial Intelligence.

Google has released all the content from its '5-Day Gen AI Intensive Course' on Kaggle for FREE! 👇 Google has made its '5-Day Gen AI Intensive Course' available as a self-paced learning guide. Here's what it covers: ✔ Day 1 - Foundational Models & Prompt Engineering: Explore the evolution of LLMs, from transformers to fine-tuning and inference acceleration. Get trained in prompt engineering for optimal LLM interaction. ✔ Day 2 - Embeddings and Vector Stores/Databases: Understand embeddings, vector search algorithms, and their real-world applications with LLMs, including tradeoffs. ✔ Day 3 - Generative AI Agents: Learn to build AI agents by mastering their core components and iterative development. ✔ Day 4 - Domain-Specific LLMs: Dive into specialized LLMs like SecLM and Med-PaLM, with insights from the researchers who built them. ✔ Day 5 - MLOps for Generative AI: Adapt MLOps practices for Generative AI and use Vertex AI tools for foundation models and generative applications. Here's the link: https://lnkd.in/dGfBNpWt --- 👉 Get free resources, curated articles, and expert tips on Data and AI: https://lnkd.in/e7EunZck #python #data #ai #machinelearning #programming

"Thrilled to share that I’ve earned a badge in TensorFlow, marking another step forward in my AI and machine learning journey! Excited to keep learning and building innovative solutions. 🚀 #TensorFlow #AI #MachineLearning #EDUSKILLS"

Excited to share my Deep Learning Repository on GitHub(https://lnkd.in/g6hDSCQU)! Is still a work in progress but feel free to explore projects, resources, and code examples covering topics like ANN, CNN, RNN, and more. Check it out and give it a star ⭐️ if you find it a helpful resource! #DeepLearning #MachineLearning #AI #GitHub #OpenSource #Code #Projects #NeuralNetworks

Bookmarking this will definitely help you in the future!

A very helpful list for those who start out and progress in ML/AI from Meri Nova !