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Essentials of deep learning and AI : experience unsupervised learning, autoencoders, feature engineering, and time series analysis with TensorFlow, Keras, and scikit‑learn / Shashidhar Soppin, Manjunath Ramachandra, B. N. Chandrashekar.

By: Contributor(s): Material type: TextTextNew Delhi : BPB Publications, 2021Edition: 1st editionDescription: 394 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9789391030353
Subject(s): DDC classification:
  • 23 006.3 s.s.e.
Contents:
1. Introduction ‡ 2. Supervised Machine Learning ‡ 3. System Analysis & Unsupervised Learning ‡ 4. Feature Engineering ‡ 5. Classification, Clustering, Association Rules & Regression ‡ 6. Time Series Analysis ‡ 7. Data Cleanup & Feature Selection ‡ 8. Ensemble Model Development ‡ 9. Design with Deep Learning ‡ 10. MLP Networks ‡ 11. LSTM Networks ‡ 12. Autoencoders ‡ 13. Applications ‡ 14. Emerging & Future Technologies.
Summary: A practical introduction to deep learning and AI emphasizing unsupervised learning techniques—including autoencoders, feature engineering, and time series analysis—using TensorFlow, Keras, and scikit‑learn. Ideal for data scientists and ML engineers. :contentReference[oaicite:1]{index=1}
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Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
Books Books Media and mass communication Library B4 006.3 s.s.e C.1 Available MA0002510
Total holds: 0

Includes bibliographical references.

1. Introduction ‡ 2. Supervised Machine Learning ‡ 3. System Analysis & Unsupervised Learning ‡ 4. Feature Engineering ‡ 5. Classification, Clustering, Association Rules & Regression ‡ 6. Time Series Analysis ‡ 7. Data Cleanup & Feature Selection ‡ 8. Ensemble Model Development ‡ 9. Design with Deep Learning ‡ 10. MLP Networks ‡ 11. LSTM Networks ‡ 12. Autoencoders ‡ 13. Applications ‡ 14. Emerging & Future Technologies.

A practical introduction to deep learning and AI emphasizing unsupervised learning techniques—including autoencoders, feature engineering, and time series analysis—using TensorFlow, Keras, and scikit‑learn. Ideal for data scientists and ML engineers. :contentReference[oaicite:1]{index=1}

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