TensorFlow is currently the most popular end-to-end platform for Machine Learning.
Here you have a free 7-hour TensorFlow 2.0 course that's packed with everything you need to get started.
(A single hour per day can get you through this course in a week! Just one week!)
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The course is structured in 8 different modules that cover different aspects of Machine Learning and focus on how to apply TensorFlow 2.0 to solve different problems.
Here is the list of modules:
1⃣ Machine Learning Fundamentals
2⃣ Introduction to TensorFlow
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3⃣ Core Learning Algorithms
4⃣ Neural Networks with TensorFlow
5⃣ Deep Computer Vision - Convolutional Neural Networks
6⃣ Natural Language Processing with RNNs
7⃣ Reinforcement Learning with Q-Learning
8⃣ Conclusion and Next Steps
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In the video description, you'll find a set of Google Colab notebooks with all the code discussed in the modules.
This is an incredible resource that you get for free and will get you started in one of the most exciting open-source tools in the market today!
If you have a list of things you've always wanted to solve, let an agent do them:
• Refactor code and ensure tests still run
• Find and fix bugs
• Close open tickets from your backlog
• Update documentation
• Write tests for untested code
• You can use it with any of the major models (GPT-X, Gemini, Claude)
• It has an option to Chat and Edit with the model
• It has an Agent mode to make changes to the notebook autonomously
Knowledge graphs are a game-changer for AI Agents, and this is one example of how you can take advantage of them.
How this works:
1. Cursor connects to Graphiti's MCP Server. Graphiti is a very popular open-source Knowledge Graph library for AI agents.
2. Graphiti connects to Neo4j running locally.
Now, every time I interact with Cursor, the information is synthesized and stored in the knowledge graph. In short, Cursor now "remembers" everything about our project.
Huge!
Here is the video I recorded.
To get this working on your computer, follow the instructions on this link:
Something super cool about using Graphiti's MCP server:
You can use one model to develop the requirements and a completely different model to implement the code. This is a huge plus because you could use the stronger model at each stage.
Also, Graphiti supports custom entities, which you can use when running the MCP server.
You can use these custom entities to structure and recall domain-specific information, which will tenfold the accuracy of your results.