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Item #:
211422156
Python, Deep Learning, and LLMs: A Crash Course for Complete Beginners
85% of respondents would recommend this to a friend
Item #:
211422156
IQD 88424
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Put in the work, and soon you will know, in concrete detail, how to create a miniature mind inside a chunk of silicon using code.
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What Stands Out
Beginner Friendly
Designed specifically for complete novices, this course simplifies complex topics, ensuring anyone can grasp the essentials of Python and deep learning without prior experience.
Comprehensive Content
Covers Python programming, deep learning fundamentals, and large language models, providing a well-rounded foundation that equips learners with in-demand skills in today's tech landscape.
Interactive Learning
Includes hands-on exercises and real-world applications, allowing users to practice coding and build confidence while reinforcing their understanding of key concepts in deep learning.
Product Details
- Python, Deep Learning, and LLMs: A Crash Course for Complete Beginners is a coding and machine learning bootcamp in textbook form. You will get hands-on experience with the Python programming language, essential math concepts, neural nets – and, by the end, you will have coded and trained a pocket-sized language model. A high school math background is all you need to get started; no prior programming experience is required. Put in the work, and soon you will know, in concrete detail, how to create a miniature mind inside a chunk of silicon using code. If that is not magic, what is?A comprehensive and engaging guide, taking the reader from programming basics all the way to large language models. It manages to be both rigorous and enjoyable.— Khaled Boughanmi, Cornell UniversityThis book stands out in clarity and effectiveness as a practical, accessible introduction to the world of AI.— Yu Ding, Stanford UniversityA great springboard into machine learning, AI, and their essential foundations – Python, matrix algebra, and statistics. Beautifully written and accessible to anyone with a basic high school math background. I've already recommended it to my students.— Kamel Jedidi, Columbia University
| Publisher | Yegor Tkachenko |
| Publication date | September 3, 2025 |
| Language | English |
| Print length | 448 pages |
| ISBN-10 | 1733902201 |
| ISBN-13 | 978-1733902205 |
| Item Weight | 1.32 pounds (600 grams) |
| Dimensions | 6 x 1.01 x 9 inches (15.2 x 2.6 x 22.9 cm) |
Who Should Buy?
-
Complete Beginners
Ideal for those with no prior knowledge in programming or deep learning, providing foundational concepts and practical projects.
-
Tech Enthusiasts
Perfect for individuals interested in exploring AI and machine learning concepts in a straightforward, engaging format.
-
Career Changers
Great for professionals looking to shift to tech roles, offering essential skills for entering the data science field.
-
Advanced Users
Not suitable for individuals with prior experience in Python or deep learning, as content may be too basic.
Product Description
Have any Query? Chat with us
Customer Questions & Answers
-
Question:
Do I need any programming experience to start this course?
Answer: No, the course is designed for complete beginners, and no prior programming experience is required. -
Question:
What background knowledge do I need?
Answer: A basic understanding of high school math is sufficient to get started. -
Question:
What will I be able to create by the end of the course?
Answer: You will code and train a miniature language model, gaining practical skills in Python and machine learning.
Neural Networks Editorial Review
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Pros
- Comprehensive beginner-friendly content
- Engaging writing style
- Includes practical examples
- Well-structured course layout
- Great support for learners
Cons
- Some readers prefer more advanced topics.
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IQD 88424
Order now and get it around Friday, October 09
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Features & Benefits
- No prior programming experience needed; perfect for complete beginners.
- Hands-on experience with Python programming and essential math concepts.
- Covers neural networks and enables you to code and train a language model.
- Written in an engaging and accessible style; suitable for those with basic high school math.
- Recommended by educators from Cornell, Stanford, and Columbia.
- A step-by-step guide from basics to advanced concepts in AI and machine learning.
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