SuperAnnotate’s Post

🔬💡 Curious about Cerebros? Discover how our open-source company can empower you to unleash the power of predictive AI to solve tangible problems, even without "big data." At Cerebros, we provide a no-code, no-operations AI platform that enables anyone to build custom predictive AI-powered applications and proofs of concept quickly and effortlessly. 🌟 Why choose Cerebros? 🔌 Harness the Power of Machine Learning: Utilize the potential of machine learning to tackle a wide range of problems, regardless of the amount of available data. ⚖️ Train with Less Data: Achieve the same accuracy with less training data and smaller scale hardware. Imagine what you could do with the money you save on GPUs! 🥂 💻 Let Us Manage Your MLops: Stay focused on your core business while we handle your MLops, ensuring seamless integration and smooth operations. 🔒 Privacy is a Priority: Enjoy complete data privacy with Cerebros. We respect your privacy and never access your data when you tell us to, so we can give you live help for your project. Ready to explore the world of AI and transform your business? Try the alpha release of Cerebros and discover how we can help you succeed in the era of AI-driven innovation. 👉 Contact us today to learn more about our platform and see how we can make your AI concept a success. https://www.cerebros.one david@cerebros.one #Cerebros #OpenSource #AI #MachineLearning #MLops

Using Databrick's open DBRX Instruct model to write code is pretty impressive. You can play with it online. It's probably one of the best code generators out there, even surpassing CodeLLaMA-70B, but it's not fine-tuned for writing software! Part of what makes DBRX powerful is that it's an MoE (mixture of experts) model with 16 experts, of which 4 are chosen for any task. Other powerful open LLMs, such as Grok-1 and Mixtral, have 8 experts and choose 2. I've been meaning to try DBRX for a while and so far, color me impressed. Reviews have been pretty solid, too. #Databricks #LLMs #AI #AIAdoption

Cognifyz Technologies Task 1 ✅ Task given: Build a machine learning model to predict the aggregate rating of a restaurant based on other features. Technology used: Linear Regression #cognifyz #cognifyzTech #cognifyzTechnologies

We are leveling up our game! 🚀🔥 Introducing our reports powered by the cutting-edge GPT-4 Turbo model – with the latest training data for unparalleled accuracy and analysis. 🌐✨ #GPT4Turbo #NextGenReports #StartupSuccess #DimeADozenAI

The Conf42 Machine Learning is happening this week. If you're plan to be there, don't miss Ricardo Covo's presentation: "Unlocking LLM Potential: A Journey with APIs" Details and registration in the post below! Check it out. https://lnkd.in/ejsugk8n

Machine Learning enthusiasts, it's trivia time! Can you name 8 of the most popular machine learning tools that are turning heads this year? DataCamp has the scoop, and we're here to test your knowledge. Here's a hint: Cloud-based innovation and open-source libraries are the game changers in 2024. Think you've got what it takes to list them? Drop your answers below. We will be adding the full list in comments soon! #MachineLearningTrivia #DataScience #MLTools #TechQuiz #ML #DataTrivia

"Wisdom of crowd" is the advantage of using Ensemble Models in Machine Learning. refers to how the ensemble models tries to avoid Overfitting after combining all received results in weak learners, and removing dependency on a particular set of features. in case regression we take the mean of all results. overwise, in classification we take majority of voting. #datascience #Ensemblemodels

A few days ago, I used MLflow and ngrok to track my dataset and model, and I'm excited about the potential it brings to machine learning! An open-source platform called MLflow provides a smooth end-to-end approach to managing the full machine learning lifecycle. Though I am still enjoying the experiment tracking stage, MLflow ensures organization and consistency in every step of model building, from experiment tracking, where parameters and metrics are simply logged, to packaging code for reproducible runs and then to model deployment. Exploring MLflow has been an eye-opening experience, revealing a robust and versatile tool that significantly enhances the machine learning lifecycle. #MachineLearning #MLflow #DataScience