Data Science & Machine Learning 101

Data Science & Machine Learning 101

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Perplexity is not your KPI
The metric that trains language models is useful, but it can lie to you the moment you start shipping LLM products, or start building AI agents.
 • BowTied_Raptor
Why LLMs change their mind
How you can build trust at scale, with these LLM models (and fight against LLM Hallucinations)
 • BowTied_Raptor
The 2 Dials that decide everything with foundation models
Architecture chooses what the model can express. Scale chooses what it can *afford* to learn.
 • BowTied_Raptor
The real differentiator behind foundation models
Architectures usually get all of the headlines, but, it's the data (and how you sample it) which decides what the model actually learns.
 • BowTied_Raptor
The AI Engineering Stack
Building AI products is less about “the model” and more about decisions, feedback loops, and boring engineering that doesn’t break.
 • BowTied_Raptor
Planning AI Applications
How to pick the right use case, set measurable goals, and avoid the “cool (but useless) demo” trap
 • BowTied_Raptor
The Rise of AI Engineering
Foundation models changed the job. Here’s what an “AI Engineer” actually does.
 • BowTied_Raptor
Data Science & Machine Learning 101
Data Science & Machine Learning 101
By Data Professionals, for Data Professionals. This is your centralized Website that has all of your data professional needs: We cover: - Money Making Guides - Job Searching - Technical Skills (R, Python, SQL, MLOps, etc...) - Industry Knowledge
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