curiousily/Deep-Learning-For-Hackers resource
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT) observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2688
- days_rel: n/a
- days_push: 2323
- n_releases_24m: 0
Adoption not part of the score
1073 stars · 433 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A free online book and collection of Jupyter notebook tutorials teaching deep learning fundamentals with TensorFlow 2 and Keras. It covers practical topics across computer vision, NLP, and time series analysis, including LSTMs, autoencoders, anomaly detection, object detection, and BERT-based intent recognition.
Use cases
- learn deep learning with tensorflow 2 and keras
- time series forecasting with lstms tutorial
- anomaly detection in time series using autoencoders
- sentiment analysis and intent recognition with bert
- how to fix overfitting and underfitting models
- hyperparameter tuning guide for neural networks
- object detection tutorial with tensorflow
- handling imbalanced datasets in machine learning
When to choose
- you want free, hands-on Jupyter notebook tutorials for TensorFlow 2 and Keras
- you are learning practical ML across vision, NLP, and time series
- you prefer runnable notebooks you can open directly in Colab
When to avoid
- you need up-to-date coverage of the latest TensorFlow or Keras APIs, as the material dates from 2020
- you need production-grade code or long-term support
- you are looking for PyTorch-based tutorials
Facets
learning-resource · maturity maintenance
machine-learning deep-learning nlp data-science deep-learning machine-learning tutorials computer-vision python cross-platform tensorflow keras jupyter-notebooks lstm autoencoders time-series-forecasting anomaly-detection object-detection sentiment-analysis bert hyperparameter-tuning natural-language-processing
5 sources
- readme: https://github.com/curiousily/Deep-Learning-For-Hackers · fetched 2026-08-28 · 7e33007eeaea
- homepage: https://mlexpert.io · fetched 2026-08-29 · 36849e3fc4f4
- site_page: https://www.mlexpert.io/academy/v1/setup-and-toolkit/local-ai-quickstart · fetched 2026-08-29 · 2b295caeb746
- site_page: https://www.mlexpert.io/academy/v1/setup-and-toolkit/langchain-quickstart · fetched 2026-08-29 · e7bd62e18b03
- site_page: https://www.mlexpert.io/changelog · fetched 2026-08-29 · 69be5f79923d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| curiousily/Deep-Learning-For-Hackers | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="curiousily/Deep-Learning-For-Hackers")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem