Machine Learning Teeta Aly Abdurrazek
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- Onderwijs
We get lost in the details. Always find ourselves not knowing where to begin or where we are heading... Lets take a bird's view on things. So we would have a better idea on how to get to where we want.
This podcast is a bird's eye view on all things machine learning. Explained to people in a hurry. ( You and me :)
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Llama 3, context window and LSTMs
We discuss three main things. First the release of llama 3. Model by meta. Second, we answer the question as to why LLMs with longer context windows are not always better. Then finally, we explain when LSTMs should be used over Transformers. Enjoy!
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Managing machine learning projects
Three points that you need to attend to, to become a good manager and to be able to make 'good' decisions that people follow. Listen to this episode to know what they are.
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What is up with AI
Open AI k, GTC, and the AI revolution. And what can we do about it?
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Artificial intelligence Value stream
AI value is created via a sequence of activities, from chip making, all through building and training foundation models, and building tools, to the application development. In this episode, we discuss these stages and what it means to the industry.
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Introduction to RAG systems (Retrieval Augmented Generation)
What are RAG systems ? Why do they matter? What are the LLM problems that are solved by RAG systems? What are the tools to create a RAG system and what does a typical system look like? Find the answers in today's episode.
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Bias and variance
Simply, what are the bias and variance? Why is there a tradeoff between them? Listen to this episode to learn about this fundamental topic which is usually asked about during data science and machine learning job interviews.