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"item_title" : "Deep Learning with Python",
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"item_description" : "Deep Learning with Python: From Basics to Real-World ProjectsAre 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 LearnDeep Learning fundamentals (AI, Machine Learning, Neural Networks)Python for Data Science (NumPy, Pandas, Matplotlib)ANN, CNN, RNN, and LSTM explained in a simple wayTensorFlow, Keras, and PyTorch with hands-on examples10 real-world projects (Image Classification, Chatbot, Stock Prediction, and more)Model deployment using Flask and StreamlitInterview questions and real-world case studiesAdvanced topics including Transformers, GANs, and Generative AIWhy This Book is DifferentUnlike many theoretical books, this guide focuses on practical implementation and real-world application.Step-by-step explanations for easy understandingHands-on projects to build real skillsIndustry-relevant tools and techniquesA complete job-ready learning approachThis book serves as a complete roadmap to becoming a deep learning engineer.Who This Book is ForBeginners starting their journey in AI and machine learningStudents preparing for technical rolesDevelopers transitioning into AI and data scienceWorking professionals looking to upgrade their skillsWhat You Will AchieveBuild deep learning models from scratchWork with real-world datasetsDeploy AI applicationsGain confidence to crack technical interviewsBonus Included30-day structured learning planInterview preparation guideReal-world case studies Start your journey today and take the first step toward becoming a job-ready AI professional.",
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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)
Overview
Deep Learning with Python: From Basics to Real-World Projects
What You Will Learn
Why This Book is Different
Who This Book is For
What You Will Achieve
Bonus Included
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.
This item is Non-Returnable
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Details
- ISBN-13: 9798255065547
- ISBN-10: 9798255065547
- Publisher: Independently Published
- Publish Date: April 2026
- Dimensions: 9 x 6 x 0.3 inches
- Shipping Weight: 0.43 pounds
- Page Count: 140
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