Keras Documentation

Category

Deep Learning

Provider

Keras

Type

course

Level

build

Topic

Deep Learning

Track

Deep Learning

Section

n/a

Format

n/a

Status

publishable

Commercial

unknown

Featured

no

Fast start

no

Sequence

n/a

Priority

n/a

Primary source

learning_paths

Sources

learning_paths

ID

dc24b278c2bb799e

TensorFlow Tutorials

TensorFlow

End-to-end TensorFlow workflows: input pipelines, training, evaluation, and serving.

PyTorch Tutorials

curated

Training loops, distributed, torch.compile, and deployment.

MIT 6.S191

introtodeeplearning.mit.edu

scikit-learn documentation

scikit-learn

Still the fastest way to build strong baselines and classical ML systems.

XGBoost Documentation

XGBoost

Strong tabular baseline models; learn training and evaluation patterns.

Transformers Documentation

Hugging Face

Train, fine-tune, and evaluate transformer models with best practices.

PyWavelets Documentation

PyWavelets

Wavelet transforms for non-stationary vibration analysis and fault signatures.

PyPSA Documentation

PyPSA

Open-source power system analysis; build grid optimization + planning pipelines.

pandapower Documentation

pandapower

Power flow and grid modeling with Python; bridges data → simulation → control.

OpenModelica Documentation

OpenModelica

Model-based engineering for energy/thermal/mechatronic systems using Modelica.

MLflow Documentation

MLflow

Experiment tracking, model registry, and reproducible ML operations.

GridLAB-D Documentation

GridLAB-D

Distribution grid simulation for demand response, DERs, and control research.