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Mashup Score: 0Agent architectures that scale - 8 day(s) ago
in the real world
Source: paulabartabajo.substack.comCategories: General Medicine NewsTweet
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Mashup Score: 0How to deploy an ML model to production - 9 month(s) ago
Let’s go step-by-step through the deployment workflow of a real-world ML REST API, following MLOps best practices.
Source: paulabartabajo.substack.comCategories: General Medicine News, CardiologistsTweet-
https://t.co/nsdSyRDnnv
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Mashup Score: 0The Machine Learning engineer of the future 🔮 - 9 month(s) ago
3 things I am currently doing
Source: paulabartabajo.substack.comCategories: General Medicine News, CardiologistsTweet-
https://t.co/t4AWtTcIFG
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Mashup Score: 0How to generate training data for your ML system - 11 month(s) ago
In real-world ML projects training data does not magically fall from the sky as in Kaggle. Instead, you have to generate it yourself. And the truth is, generating this training data takes way more time, effort and debugging than training the ML models later on.
Source: paulabartabajo.substack.comCategories: General Medicine News, Cardiologists1Tweet-
https://t.co/JPvJaEX0Hv
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Mashup Score: 0Wanna land an ML job? Then do this ↓ - 1 year(s) ago
Training Machine Learning models inside notebooks is just one step to building real-world ML services. And as exciting as it is, it brings no business value unless you deploy and operationalize the model. In this article with video, you will learn how to transform an all-in-one Jupyter notebook with data preparation and ML model training, into a fully working batch-scoring system, using the
Source: paulabartabajo.substack.comCategories: General Medicine News, Cardiologists1Tweet-
https://t.co/sH6gqgIvzj
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Mashup Score: 0How to generate a Q&A dataset in less than 30 minutes - 2 year(s) ago
Say you want to build an ML model that can act as an investing advisor. That is, a user sends basic information about himself/herself “I am a 25 year old software engineer with a stable income. I want to start investing in stocks for long-term growth. Where should I begin?”,
Source: paulabartabajo.substack.comCategories: Cardiologists1, Latest HeadlinesTweet-
https://t.co/avwMpmZfZq
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Mashup Score: 0Fine tuning pipeline for open-source LLMs - 2 year(s) ago
This is Lesson 1 of the Hands-on LLM Course, a FREE hands-on tutorial where you will learn, step-by-step, how to build a financial advisor, using LLMs and following MLOps best practices. This course is not about building a demo inside a Jupyter notebook, but a fully working app, using the
Source: paulabartabajo.substack.comCategories: Cardiologists1, Latest HeadlinesTweet-
https://t.co/Rd17i448Bc
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Mashup Score: 0Fine tuning pipeline for open-source LLMs - 2 year(s) ago
This is Lesson 1 of the Hands-on LLM Course, a FREE hands-on tutorial where you will learn, step-by-step, how to build a financial advisor, using LLMs and following MLOps best practices. This course is not about building a demo inside a Jupyter notebook, but a fully working app, using the
Source: paulabartabajo.substack.comCategories: Cardiologists1, Latest HeadlinesTweet-
https://t.co/Rd17i448Bc
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Mashup Score: 0Real-World Machine Learning | Pau Labarta Bajo | Substack - 2 year(s) ago
Every Saturday Morning. Click to read Real-World Machine Learning, by Pau Labarta Bajo, a Substack publication with thousands of subscribers.
Source: paulabartabajo.substack.comCategories: Cardiologists1, Latest HeadlinesTweet-
Real-World Machine Learning | Pau Labarta Bajo | Substack https://t.co/IQR1WW2SYi
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Mashup Score: 0Don't know how to deploy an ML model? - 2 year(s) ago
Your ML model, no matter how accurate it is, has a business value of $0.00, as long as it stays confined in the realms of Jupyter. If you want to build Machine Learning solutions that bring business value you need to go a few steps further, aka deployment
Source: paulabartabajo.substack.comCategories: Cardiologists1, Latest HeadlinesTweet-
https://t.co/hUqNkizmVY
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https://t.co/EyeRqPRshJ