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Longer reads that go with the videos: how large language models work, how to choose a metric, and what the job of a data scientist is becoming.
career
What Is Left for a Data Scientist When AI Writes the Code?
AI now writes the code and AutoML builds the model. What stays human for a data scientist: the DIKW climb from data to wisdom, the consulting layer of DMAIC, and data science as…
LLMs
Representation Models - Text Classification
How representation models turn text into numbers: what BERT is, how masked language modelling and next sentence prediction train it, and how sentence transformers power text…
LLMs
Foundation Models - LLMs
What a foundation model is, explained with a restaurant's base gravy, plus how large language models and the transformer behind them work, and the main types of LLMs.
machine learning
What metrics to be chosen for classification modelling?
Accuracy, recall, precision or F1? The confusion matrix made simple, and how to choose one metric for cross-sell, customer attrition and fraud models by starting from how the…
career
Does Data Scientists need to learn programming?
Coding is not copy and paste from ChatGPT. Why data scientists still need to understand the full cycle of programming: what to code, how to code, testing, and coding within…
career
Does Data Scientists need to understand Domain Knowledge?
A retail stocking case from my own work shows why a forecast alone doesn't answer the business question, and why data scientists need domain knowledge before they build models.
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