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Deep Learning with Python: Hands-On Guide with 10 Real-World Projects Neural Networks, CNN, RNN, LSTM, TensorFlow & PyTorch (2026 Edition)
Paperback
Series: The Complete Data Science & AI Engineering, Book 3
Publisher: Independently Published
Published: Apr 5 2026
Pages: 140
Weight: 0.43
Height: 0.30 Width: 6.00 Depth: 9.00
Language: English
Are you struggling to understand deep learning concepts and apply them in real-world scenarios?
Do you want to build AI models, work on real projects, and become job-ready?
This book is your complete step-by-step guide to mastering deep learning using Python-even if you are a beginner.
What You Will Learn
- Deep Learning fundamentals (AI, Machine Learning, Neural Networks)
- Python for Data Science (NumPy, Pandas, Matplotlib)
- ANN, CNN, RNN, and LSTM explained in a simple way
- TensorFlow, Keras, and PyTorch with hands-on examples
- 10 real-world projects (Image Classification, Chatbot, Stock Prediction, and more)
- Model deployment using Flask and Streamlit
- Interview questions and real-world case studies
- Advanced topics including Transformers, GANs, and Generative AI
Why This Book is Different
Unlike many theoretical books, this guide focuses on practical implementation and real-world application.
- Step-by-step explanations for easy understanding
- Hands-on projects to build real skills
- Industry-relevant tools and techniques
- A complete job-ready learning approach
This book serves as a complete roadmap to becoming a deep learning engineer.
Who This Book is For
- Beginners starting their journey in AI and machine learning
- Students preparing for technical roles
- Developers transitioning into AI and data science
- Working professionals looking to upgrade their skills
What You Will Achieve
- Build deep learning models from scratch
- Work with real-world datasets
- Deploy AI applications
- Gain confidence to crack technical interviews
Bonus Included
- 30-day structured learning plan
- Interview preparation guide
- Real-world case studies
Start your journey today and take the first step toward becoming a job-ready AI professional.
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