455 CARDS · 41 WEEKS · EVERY SOURCE THE PLAN NAMES
Every video, chapter, paper and repository in the programme, as one card each, with the time it costs and why it is there. Filter by how long you have.
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Monday build block · Read it inside Monday's build block
Build-block reading · Luttmann et al. (2012), "Soft sensors in bioprocessing: a status report and recommendations", Biotechnology Journal 7(8):1040-1048. The reference framing for your soft-sensor section
In: LABLOOP-W08 Notebook
Saturday sandbox · after 3Blue1Brown Neural Networks ch. 3-4 ("Backpropagation, intuitively"
Stanford CS231n notes "Backpropagation, intuitions" (cs231n.github.io/optimization-2) — a classic written explanation
In: LABLOOP-W08 Notebook
Read engine.py (~100 lines); run demo.ipynb in Colab; then close it and rewrite from memory on Saturday
In: LABLOOP-W08 Notebook
Lecture notebooks under lectures/micrograd; follow along with the video
In: LABLOOP-W08 Notebook
Python quickstart regression; train on your unfolded features with batch-wise CV
In: LABLOOP-W08 Notebook
Colab: chapter 1 "The g-h filter". The intuition behind estimating a hidden variable from noisy sensors, which is what a soft sensor does
In: LABLOOP-W08 Notebook
Browse the model zoo for industrial soft sensors; note which baselines they compare, to justify your LightGBM vs PLS choice
In: LABLOOP-W08 Notebook
quarto create project manuscript; build a PDF with one figure regenerated from code
In: LABLOOP-W08 Notebook