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[Migrated from GHES] Original #315 by @jaboumal
- Als System möchte ich eine Endpoint GET /events/{id}/statistics bereitstellen (API schon definiert)
- Nur Member mit der nötigen Berechtigung können ...
backend
Estimate 2
MaloJaboulet
Build CNN from scratch. Understand conv layers, pooling, batchnorm. Target 85% accuracy.
kaggle
phase-1
hg1112
Implement neural net in raw NumPy or minimal PyTorch (no nn.Sequential shortcuts). Target 98% accuracy.
kaggle
phase-1
Build baseline with logistic regression + small MLP. No AutoML or sklearn pipelines.
kaggle
phase-1
[Migrated from GHES] Original #314 by @jaboumal
- Als System möchte ich einen Endpoint PUT /events/{id}/participants/{memberId} bereitstellen (API schon definiert)
- Admin soll auch für eine Person ...
backend
Estimate 3
Convolutional networks, modern CNN architectures, RNNs, LSTMs, GRUs.
book
phase-1
Dive into Deep Learning. Linear nets, MLP, numerical stability, computational performance.
book
phase-1
[Migrated from GHES] Original #313 by @jaboumal
- Als System möchte ich einen Endpoint GET /events mit Pagination und Suchfunktion erstellen
- Als System möchte ich pro Event festhalten, welche Gruppen ...
backend
Estimate 3
KMM
Build a mini GPT: multi-head self-attention, positional encoding, transformer blocks. Train on Shakespeare dataset.
exercise
phase-1
Extend bigram to MLP. Implement embedding lookup, hidden layers, output projection.
exercise
phase-1
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