Deep Learning Illustrated (30 reviews: 4.9 out of 5 stars)
“Over the next few decades, artificial intelligence is poised to dramatically change almost every aspect of our lives, in large part due to today’s breakthroughs in deep learning. The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come.” ~ Tim Urban, writer and illustrator of Wait But Why
“This book is an approachable, practical, and broad introduction to deep learning, and the most beautifully illustrated machine learning book on the market.” ~ Dr. Michael Osborne, Dyson Associate Professor in Machine Learning, University of Oxford
“This book should be the first stop for deep learning beginners, as it contains lots of concrete, easy-to-follow examples with corresponding tutorial videos and code notebooks. Strongly recommended.” ~ Dr. Chong Li, cofounder, Nakamoto & Turing Labs; adjunct professor, Columbia University
“It’s hard to imagine developing new products today without thinking about enriching them with capabilities using machine learning. Deep learning in particular has many practical applications, and this book’s intelligible clear and visual approach is helpful to anyone who would like to understand what deep learning is and how it could impact your business and life for years to come.” ~ Helen Altshuler, engineering leader, Google
“This book leverages beautiful illustrations and amusing analogies to make the theory behind deep learning uniquely accessible. Its straightforward example code and best-practice tips empower readers to immediately apply the transformative technique to their particular niche of interest.” ~ Dr. Rasmus Rothe, founder, Merantix
“This is an invaluable resource for anyone looking to understand what deep learning is and why it powers almost every automated application today, from chatbots and voice recognition tools to self-driving cars. The illustrations and biological explanations help bring to life a complex topic and make it easier to grasp fundamental concepts.” ~ Joshua March, CEO and cofounder, Conversocial; author of Message Me
“Deep learning is regularly redefining the state of the art across machine vision, natural language, and sequential decision-making tasks. If you too would like to pass data through deep neural networks in order to build high-performance models, then this book—with its innovative, highly visual approach—is the ideal place to begin.” ~ Dr. Alex Flint, roboticist and entrepreneur
You can get at least 100 book titles on deep learning. In my personal opinion, Jon Krohn is an artist and I have never seen any other book better than his book to demonstrate the complex deep learning methods. This is a must for beginners to get knowledge in deep learning. — Subrata Bhowmik, PhD
I buy and read a lot of books - especially books on #AI and this one is one of the best I can recommend. I first noticed the book due to the cover (of a Trilobite!) I practically live off Attenborough and can recognise a Trilobite from about age 10. And I think its a great way to explain #deeplearning #machinelearning AI by thinking of the evolution of the brain from the simplest lifeforms (like Trilobites) and then considering the evolution of the eye (sort of like the approach in the Blind Watchmaker) and separately, one of the authors Jon Krohn, Ph.D. contacted me through a #universityofoxford connection (Jon has an Oxford neuroscience background). Finally, I saw Kirk Borne endorse the book in a big way! So I bought it and it does not disappoint. A comment on Amazon says that this book is a stunning achievement! and I very much agree. — Ajit Jaokar, University of Oxford Artificial Intelligence Course Director on May 11, 2020
This book got me into Deep Learning. This is a high-level overview that any software engineer will desire as we try to understand “this new world” (even as of 2019). The terms in new-world are used in multiple Medium articles, and github.io pages and github.com READMEs, and we wonder what any of these have to do with solving the problem, how does it fit in, etc. This book took a top-down approach to explain it all and help me made sense of every article that I read about Deep Learning, Convolutional Neural Networks, and Artificial Intelligence as of 2019. I like to thank the Authors for their invaluable contribution to this field. — Senthil Kumaran Obla Ramesh Babu on November 27, 2019
Great guide to deep learning concepts. I had my doubts that a book about deep learning that doesn't contain rigorous mathematical treatment would be able to explain the concepts on more than a superficial level. I was defininately wrong. This is one of the best introductions to what deep learning is all about. The concepts are explained thoroughly, with small example neural networks that really help you work through the mechanics. Read this book to understand the core concepts, find another to supplement then detailed mathematics. — Francis Huynh on November 22, 2019
Great book! I already got the 2nd copy, gave the first one away. I read it in a week! This hasn't happened in a while. I will read it again and go through all the exercises. I already have bought a bunch of references mentioned in the book. I have a concrete project I want to work on and I needed a quick overview what is possible. This book gave me exactly what I needed. I liked the style of the chapters with the summary and the ever growing list of key concepts. Great buy. — carpitol on November 13, 2019
This book should be required reading- Highly recommend for all levels. As an AI practitioner, I was very impressed with this book, and truly enjoyed reading it. This is an excellent illustrated book on Deep Learning which covers a broad range of AI topics in an accessible and engaging way. Jon Krohn does an excellent job of introducing, weaving together, then applying concepts in an immediately usable way. The illustrations are very effective for visual learners, and makes complex concepts accessible to beginners, and also serves as a reference for experienced developers. I would recommend this book to anyone looking for a practical guide to deep learning. — Minerva Tantoco on November 11, 2019
Must read! Just finished this excellent book! For those interested in a good introduction on the field of Deep Learning this is the perfect starting point. The distinctive feature of the book is the step-by-step presentation of each subject that leaves no room for floundering. While reading the text I got questions that most of the times were answered in the subsequent lines. This made me confident that I understood every aspect of the presented topic. The illustrations are also excessive and follow the same step-by-step approach. The book includes many hints for creating DP models and intuitively understand the options underneath. In terms of organization and language the authors did a great job and complemented their material with Jupyter notebooks. A 5-stars (more like 6-stars) book indeed. — Amazon Customer on November 4, 2019
Perfect compliment to great weather and ice cream! This book is excellent for the beginner, intermediate, and advanced programmer. I used this book as a compliment to Jon's deep learning course back in 2018. And a year later, I still go back to it for a refresher. Page 91 is definitely my favorite page of the book. wx = b. remember that equation and remember it well. Jon is an excellent lecturer and this book is a great representation of the theory behind deep learning and Jon creates a tremendous source for all levels to enjoy! If you're a beginner, don't be afraid of deep learning!!! I wrote my first hello word function about 6 months before I started reading Jon's material. I was able to even create my own small project as well! I highly recommend this book to all! — Hank Yun on October 25, 2019
Excellent and intuitive description of deep learning — Antonio M. on October 23, 2019
Engaging for anyone, at any level, as long as you have an interest in AI, you'll love it. This book is really clear, beautifully illustrated, and easy to read. Even for someone with no background in computer science, it's interesting and grabs your attention! — Shannon Cutt on October 15, 2019
Wonderful Book. Amazingly thorough, and all of the many illustrations help keep things fun and interesting. — Jeff Fenster on October 8, 2019
Light hearted, deep teaching. This book takes you on a historical journey, a conceptual journey and delivers the reader the material for becoming a real practitioner. And... it is done with such style! I loved it. — Gareth on October 8, 2019
Great for a visual learner! The illustrations are an excellent visual aid to the material. A great resource for anyone interested in AI/deep learning. — Amazon Customer on October 8, 2019
Fantastic intro book to Deep Learning. This book removes any roadblock you may have when trying to understand the concept of deep learning. So far, a great read! Highly recommend it! — Lani on October 8, 2019
Awesome introduction into Deep Learning. Great book. Easy to read and follow. Dr Jon Krohn does a great job handling a complex topic. — Kenny on October 8, 2019
Complex ideas simply explained. Great book that gives a clear overview of a complicated subject. — RU on October 7, 2019
An excellent resource! This title is a great resource for those looking to understand deep learning. The illustrations are helpful and aid in cementing a richer understanding of the content, and the background context surrounding biological motivations for the tools and techniques enables a greater appreciation of the field. I enthusiastically recommend this book to any and all who are interested in the topic of deep learning! — Vince Petaccio on October 3, 2019
Solid and Fun Deep Learning Book. I took an online course taught by Jon Krohn and thoroughly enjoyed it. I was also notified about the pre-release version of the book. Having read the first few chapters of the book, I found the material both engaging and informative. There are web-links to interactive material to explore on your own as well as links to other sites that can provide you additional learning materials., should you want to explore topics in greater detail. I will come back and revise the review once I am able to get through the entire book, but I highly recommend this book for those interested in learning about Deep Learning (and actually applying the material taught in the book). — Alex Verrigni on September 18, 2019
For programmers interested in Deep Learning. Excellent book for people with programming skills interested in Deep Learning. The authors do a great job explaining both the context and modern application of Deep Learning technologies in an approachable–and entertaining–way. — Sangbin Lee on September 12, 2019
An appreciable piece of knowledge & art. I buy many books every week and I spend half my time reading mostly AI related material, but I think I have not been touched by I book like that since my childhood, when I was reading the illustrated "Encyclopédie de la Jeunesse". This book is a piece of knowledge and art, it covers all you need to know and gives you a very welcome general & comprehensive view of the field, and most of all, it gives context and tells a story. I strongly recommend this read to whoever is interested by the field, regardless of your level of expertise. — M. Lamrani on September 2, 2019
I will recommend everyone to read this book. One of the best book on deep learning. — Deepika Bansal on August 27, 2019
Jon's book is a great resource for anyone trying to learn about machine learning and deep learning. Not only is the book extremely well written, Jon also attaches coding examples in each section of the book which help illustrate all the theory. Must have for AI enthusiasts! — Akai Joy on August 9, 2019
It’s a great book mixing theory with practical learning! — Ramune on July 26, 2019
One of the best books on deep learning. — Arnab Mohanty on June 4, 2019
This book is a stunning achievement, written with precision and depth of understanding. It entertains you and gives you lots of interesting information at the same time. I could never imagine understanding and gaining scientific knowledge, namely “Deep Learning” can be this much fun! Reading the book is a pleasure and I highly recommend it. — Maryam Khakpour on May 18, 2019
Excellent book for people with programming skills interested in Deep Learning. The authors do a great job explaining both the context and modern application of Deep Learning technologies in an approachable–and entertaining–way. — Sangbin Lee on May 2, 2019
This book has been great for me. — Brandon Hodges on March 13, 2019
This book removes any roadblock you may have when trying to understand the concept of deep learning. So far, a great read! Highly recommend it! — Lana Tayara on December 6, 2018
This title is a great resource for those looking to understand deep learning. The illustrations are helpful and aid in cementing a richer understanding of the content, and the background context surrounding biological motivations for the tools and techniques enables a greater appreciation of the field. I enthusiastically recommend this book to any and all who are interested in the topic of deep learning! — Vince Petaccio on December 6, 2018
GREAT BOOK! — Sarah Y. on December 6, 2018
Great stuff. — Mark Bragg on December 5, 2018
In-classroom Deep Learning course at the NYC Data Science Academy
The Deep Learning course at NYC Data Science Academy provides a solid introduction to the fundamentals and application of the suite of deep learning models. The instructor, Dr Jon Krohn (DPhil, Oxon), has a talent for teaching deep learning in an accessible, conceptual manner and for demonstrating the wide range of applications that benefit from these neural network architectures. The course content covers the basics of neural networks from the basis of neurons, activation functions to shallow / dense layers and to more advanced models including convolutional neural networks (CNNs), long short-term memory (LSTMs), auto-encoders, Generative Adversarial Networks (GANs) and reinforcement learning. Course readings are taken from the recently published Deep Learning Illustrated book, co-authored by the instructor. There is heavy emphasis on coding using TensorFlow 2.0 and Keras in Jupyter Notebooks along with an introductory lesson on PyTorch. Dr Krohn has a very extensive code repository featuring a myriad of deep learning architectures. The lessons guide us through model code line by line, gradually building up in model complexity across the weeks. Dr Krohn discusses model tuning and addresses common model fitting pitfalls including preventing over-fitting and exploding / vanishing gradients. By the end of the course, the students are able to showcase projects fitting several advanced architectures including CNNs, RNNs and LSTMs to interesting datasets for image recognition, speech recognition and natural language processing. This course is highly recommended if you are looking for a comprehensive and stimulating face-to-face introduction to one of the most revolutionary methodologies in machine learning today. — Dr. Edward Tong on Dec 30, 2019
I took Jon Krohn’s deep learning course in the fall/winter of 2019. Jon is that rare communicator with the aptitude to succinctly explain rigorous and complex topics in a digestible fashion. His course is an ambitious undertaking, but Jon makes the subject matter as accessible as it’s likely to be. After the course, you’ll not only possess a foundational understanding of neural nets, but also Jon’s compilation of resources for your continued self-experimentation. Jon’s approachability as an instructor, his unabashed love of this cutting-edge science, and his genuine interest in seeing his students advance their understanding could not place you in better hands. — Justin Ng on Dec 22, 2019
You can read books about deep learning and in fact the instructor Jon Krohn has a new book out as well. However, there is a gap between reading and understanding conceptually and writing code to solve a real-world problem. This course completely fills the gap. The instructor does give you the conceptual foundations, assuming no prior knowledge. I did have some prior knowledge, but still the class is self-contained. I would say 30-40% of class time is spent discussing code that solves a practical problem. I think this is the perfect balance: you can't delve more into code without a global understanding why all those parameters may be required and you can't delve deeper into theory without neglecting the practical question of "where do I begin". The instructor is very personable and easy to approach about his own experience in the industry. — Marius Popa on May 1, 2019
I took NYC Data Science Academy's deep learning course, taught by Jon Krohn. Jon is a terrific teacher, and I would heartily recommend this course! Jon had tremendous enthusiasm and patience for questions while still keeping us on track with the schedule. He really broke things down into bite-size, understandable pieces, while still covering a lot of breadth and depth. I appreciated Jon making available his draft book, this really complemented the lectures. I liked the format of once-a-week lessons because it gave time for concepts to sink in and to practice things with my own data in between sessions. I appreciated that Jon made time to troubleshoot challenges we experienced in our own projects. The course was both a great introduction to concepts and to some of the ways people are applying deep learning; here examples from Jon's day job were valuable. One aspect of the course that was very helpful was that Jon set up a Docker environment for us, and shared very clear instructions for getting our computers set up with it in advance. We were all ready to go from the start. I'm all the more grateful for Jon having set that up after recently spending half of a workshop (run by a different data science academy) wrestling with [setup]. The Jupyter notebooks all just worked, so we could focus on learning. — Dr. Ilya Fischhoff on February 3, 2019
The Deep Learning course conducted by Jon offers a great learning experience for people starting with their journey on deep learning. Jon starts with the basics and gradually moves on the advance topics. The topics are shared well in advance so that we can prep ourselves before the class. Jon mixes the intuitiveness and the mathematics on the topic in a balanced way. As part of the course, Jon also encourages everyone to do a project and offers great support. My only piece of constructive criticism (which by the way is not at all a criticism) would that the last class is a bit heavy content wise and hence breaking it down a little would be something to consider. Overall, I would highly recommend this course to someone who wants to start with deep learning.— Navin Krishnakumar on December 20, 2018
The Deep Learning course by Jon Krohn at the NYCDSA has been one of the best courses I've taken. With a focus on projects, Jon teaches students the tools they need to create their own deep learning project at any level. When I say at any level I really mean at any level. I'm a biology major originally and printed my first 'hello world' a year ago. Even with my very limited coding and programming background, I was able to complete a deep learning project involving creating my own labeled dataset and a convolutional network classifier… I really appreciated his course structure as he drills in the beginning of class what he terms 'arsenal' deep learning terms and theories which I believe played a huge role in my ability to even create a project. The course is just 5 weeks so a lot of information is packed in weekly, but it really is for deep learning hopefuls of all levels from the basics of Keras in machine vision or natural language processing to the intricacies underneath TensorFlow… Jon was insightful, responsive, and encouraging to his students throughout the course. He often broke down difficult theories and concepts on the whiteboard with easy to understand examples and drawings which I found very helpful. I am looking forward to more classes from him! — (Hank) Ha Seon Yun on December 15, 2018
Jon's course on Deep Learning was great. It started with the basics including the background theory, then progressed to looking at concepts in different fields like computer vision, NLP, reinforcement learning, etc. It required a bit of programming experience, but not too much for those worried about their experience level. Likewise for math chops - having a basic understanding of linear algebra helps in understanding the theory, but it's not required to use it in practice. Following along in class was great, and the materials he had available for learning outside of the classroom were fantastic as well (i.e. his materials on GitHub, links from his presentations to outside materials, etc.) If Jon does a course on Intermediate/Advanced Deep Learning, or deep dives on topics within deep learning, I'll definitely be on the waiting list! — Zach McCormick on December 14, 2018
Great intro to deep learning! I enrolled in this course with some working knowledge of machine learning, but no prior experience with neural nets or coding in Python. I thought this course was a great introduction to the topic, especially given that we were able to preview the instructor's forthcoming textbook on deep learning. Being able to go back and forth between the book and the lecture notes, and walk through the code together as a class, was really useful for solidifying newer concepts. The instructor was really approachable and friendly, and was good at drawing from various strengths that were present from other participants in the class. A great course, I enjoyed it. Would recommend to anyone who wants to get a high level intro to deep learning in a more structured setting than just an online course. — Barbara on October 1, 2018
Thank you to Jon Krohn for his approach to teaching the lectures and for his systematic organization of all his materials. Also, for being very attentive to the questions and trying to get back with constructive help ASAP. — Alexey Malafeyev on September 18, 2018
Jon Krohn is an amazing instructor. I am a Web Engineer and have zero to little idea about Deep learning. For me to sit in class and not be intimidated by the course and fundamentals of Deep learning is a testament to Jon's teaching. The course is a really good starter kit for anyone looking to get into Deep Learning and AI in general. There is some knowledge of python that might be useful to have prior to taking this course as there are many live exercises worked on python. You will be given an opportunity to complete a project during the course which I suggest you do as it will make you apply the skills you review right after class that will make learning the concepts more enjoyable. All in all, I will 100% recommend this course for anyone who is looking to get a thorough overview of the fundamentals and philosophy of Deep Learning and its future. — Deekshita Amaravadi on September 17, 2018
I highly recommend the deep learning course for anyone. Jon is the best teacher. He actively responds to your questions and teaches in an easy-to-understand way. I am very happy that I made the right decision. I started from zero and now have an application idea for my research. — Yun Wang on September 3, 2018
Jon's course serves as an excellent introduction to neural networks, Keras and TensorFlow. The course begins with Jupyter notebooks that Jon has already set up, so getting started couldn’t be easier. He proceeds to cover the most common use cases for deep learning, including image classification, text classification and image generation, striking a nice balance between the breadth of topics covered and the nuts-and-bolts of neural networks. By the end of the course you will have seen working code for a number of different types of nets, including CNNs, LSTMs, and GRUs. There are a number of ways to introduce oneself to the complex topic of deep learning—with a book, an online course, or an in-person course like Jon’s. Price, of course, is the biggest drawback to a face-to-face course like this one. In making my own decision, I decided that the distraction-free, intensive environment that an in-person course offers was worth the extra cost. In retrospect, I think I made the correct decision. — Jerry Kurlandski on May 29, 2018
For those looking to break into the field of AI/Deep Learning - I highly recommend the Deep Learning course as the starting point... Building a foundational base in DL was what I was looking for from this course; and it was what this course delivered. You will touch all the core areas of DL, from feedforward neural nets to RNNs, CNNs even GANs and RL while covering applications such as computer vision and natural language processing. Most importantly, throughout the course Jon covers the nuts and bolts of each model in such a way that you can understand the theory without a PhD— all the while implementing DL models yourself in class to cement what you learn as you go. Best of all, you’ll be in a group with bright individuals as eager to learn as you. With some work and effort out of class, with this course you can go from zero to confidently building you own deep learning models within a month. — Chris Urrea on May 19, 2018
Amazing introduction to Deep Learning. The course curriculum provides a solid understanding of core theoretical concepts and their practical applications. The best part of the course was that the latest papers and research (as resent as Jan 2018) were discussed by Jon who also shared his experience and best practices. Would strongly recommend the course for anyone who has some background in data-/programming-related work and wants to break into deep learning. — Sudhanshu Chib on May 14, 2018
This Deep Learning Course Was a Joy. I think the course did a great job of introducing students to the deep learning landscape, helping us understand what makes deep learning techniques excel at a wide range of tasks and then diving into the code (Keras, TensorFlow) to show us how to spin up various networks (NN Regressors, NN Classifiers, Convolutional NN, RNN's, Reinforcement Learning networks, GANs). Jon is a Ph.D. neuroscientist and one thing I particularly enjoyed about the course was that Jon drew upon his background to connect the artificial neural network content with its biological inspiration. Students are encouraged to complete a deep learning capstone project for the course and there were plenty of opportunities to get valuable feedback and mentorship when we got stuck, which was great. Overall, it was time and money well spent. — Michael Roman on May 10, 2018
I took the class with Jon Krohn and could not be more pleased. Jon has a rare ability to take a complicated subject and reduce it to its fundamental elements. Instead of approaching the problems with math alone, Jon spends time crafting examples and analogies to make sure students understand the actual building blocks conceptually. That produces an epiphanic experience where we were able to visualize what is happening behind the scenes. The concepts I’ve learned in this class is something I plan to apply to real-world problems and therefore highly recommend this class to anyone who wants to learn about this field. — Khanan Grauer on March 20, 2018
I attended the Deep Learning course at the NY Data Science Academy that was taught by Jon Krohn during October 2017 - December 2017. Overall it was exactly what I hoped it would be. It gave me a strong foundation of all the core deep learning concepts. The class was hosted on every other saturday which allowed enough time to fully explore a particular topic between classes. Jon made a particular effort to keep the material simple and explained the concepts intuitely rather than with complicated math. Jon has great understanding of the content and is well prepared for each lesson. I thoroughly enjoyed the class and it has motivated me to pivot my career into deep learning. I would recommend this class to anyone who is passionate about deep learning but don't know where to begin. It is also great for anyone who has worked with some but not all of the deep learning techniques. — Mahipal Singareddy on February 9, 2018
Going into the course, I was slightly afraid that I would get lost in the mathematical concepts, and may not have the necessary technical know-how. Turns out I actually had a ton of fun with this class. Jon's class preparation goes beyond any educator I have worked with. He is able to illustrate the complex concepts with super-easy-to-understand visulizations and/or videos. When it came to application, he walked us through, line-by-line, all the code, and incrementally built up the complexity. Honestly, I can't believe we were able to cover convolutional models, recurrent models, generative adversarial networks, and deep reinforcement learning in such a short time. There was ample amount of sample code in Jupyter Notebooks to follow. Aside from that, Jon was just super nice guy and very humble. The course is beneficial to those that just want to learn in more detail how Artificial Intelligence can be applied, and also those that are more senior data scientists that want to add Deep Learning techniques to their tool-belt. — Richard Sheng on February 9, 2018
Deep Learning with TensorFlow video tutorials (72 reviews: 4.9 out of 5 stars)
It gives a very good top-level understanding of the deep neural network, implementation basics, TensorFlow. Nice structured course and very concise. this surely gives a very right direction to deep dive into this. kudos to the instructor. — Alok Kumar Sinha on Oct 20, 2019
If you are beginning with Neural Networks and want to know the topics that need to be learnt, or you want to revise the topics this is the Best video series! — saitejam on August 22, 2019
Great course, very good to get started with Keras and Tensorflow! — Joachim Hagege on February 14, 2019
Very well-explained. Love his style of teaching. Many concepts need to be understood in parallel and he does it beautifully. — Bonson Sebastian Mampilli on February 4, 2019
Great! — Baku Ikhlas on February 2, 2019
This is an exceptionally well-structured and presented tutorial. I have a bit of a background in traditional machine learning, but am by no means an expert. For me this was perfect. I am looking forward to the DL for NLP tutorial by the same author. — Thilo Gotz on January 17, 2019
Great place to start learning. So many useful references. — Abhir J. on December 31, 2018
So simple. Great teaching and very well structured. It serves as a refresher or an introduction to Deep Learning. — Rangel Alvarado on December 30, 2018
Great teaching! You made deep learning so simple and easy to learn. — Amrendra Kumar on December 10, 2018
Awesome teacher! Great structure of lessons. Great exercises! Altogether, top notch. — Vuk Radovic on November 2, 2018
Thank you for your great videos, you have no idea how much they helped me to learn about Deep Learning. I was hopeless after searching for three months, but then a professor in my university sent me a link to your videos. — Ramin Saljoughi Nejad on August 23, 2018
Great lecture for beginners and easy-to-follow code. — Suraj Shrestha on August 18, 2018
[Good] value for time — Husain Zafar on July 22, 2018
In-depth coverage, but described in a way that is great for beginners. — Luke Rasmussen on June 15, 2018
Super material!— Sumana Pal on June 4, 2018
Super deep dive, with explanations that are so easy to understand. — Truong Le on May 23, 2018
Awesome lectures! — Siddarth Jain on May 13, 2018
Really good. Thanks for improving my understanding of artificial neural networks. — Sriram Nathan on May 7, 2018
Great videos... Before I took this course, I never used Keras and TensorFlow. now, I can read the code and understand what is happening. Thanks Jon. — Ryan on April 25, 2018
Very good. — Aminoosh on April 25, 2018
Best introduction I have seen for this topic. — student on March 18, 2018
Perfect to get you up and running. Great instructor. — William on March 13, 2018
Probably the best introduction course out there for Deep Learning. Really helps build the concepts from the ground up and starts with basics and covers a lot of ground into the deep. A litmus test of any good introductory course like this is to take hard-to-explain concepts and break them down into simple known concepts, which Jon does an excellent job of. He clearly knows this subject inside out and is able to bring the learner along with him in the journey. Must watch for anyone getting started from ground 0 in Deep Learning. — Neelesh on March 8, 2018
Very well explained! — Suresh Kumar Muthumal on March 2, 2018
Great step-by-step 'til you reach a good understanding for more complex architectures. — Mohamed Bahgat on February 5, 2018
Great course. — Alvaro Fuentes on January 18, 2018
Best course I've seen on Deep Learning: Explains theory very well with whiteboard and appeals to tuition; real code walking through each step; shows the process and impact of tweaking/tuning models — Brian Pfeil on December 15, 2017
The teaching was very good, content-wise and thanks a ton for putting all the code on GitHub! — Abhiram Iyenger on November 21, 2017
Very well done, the combination of whiteboard lesson and hands on code was really good. The focus of keras before going to pure tensorflow made it much easier to see the concepts. — Mats Bengtsson on November 19, 2017
Excellent - Jon has explained all the Neural Networks concepts in a very simple and easy way. Strongly recommended this course for beginners. — Vinod Basantani on November 7, 2017
I like that Jon includes all of the Docker setup in the Github site: One of the most challenging things I’ve run into is getting all of the many software packages working together. The Docker approach makes this much simpler. I’m looking forward to more, deeper (no pun intended) courses from Jon.— wjk5828 on October 31, 2017
Both just enough theory and lots of it. Really opens the world of machine learning for the student. Great work!— Nickolas Nikolic on October 23, 2017
Great course! Very well presented and explained! — P. Kovacs on September 10, 2017
Loved it. Look forward to more courses coming up from Jon. — Denzil Sequeira on August 25, 2017
I took this course as a refresher, but I still found the fundamentals to be explained in the best and simplest way. — Srinivas Rangu on August 19, 2017
Great course and great delivery. The material was definitely well presented by Dr. Krohn in a way that anyone can understand. I really like the way that all supplemental information is also available at GitHub. This really helps with hands-on learning. Kudos to Dr. Krohn!— Omar Santos on August 11, 2017
Thanks a bunch for the wonderful material presented exceptionally well, Dr. Krohn. — Basab Dattaray on August 7, 2017
Really good videos! Thank you Jon! — Fabio Salvi on July 31, 2017
Live Workshops and Talks
Please extend my massive thanks to Jon for such a compelling speech - we've never had anything like that in the 4 years I've been around this space 🙂 — Mara Navarro on June 22, 2023
Smart guy. Well prepared for class. Materials and Labs are well thought out. Explanations very clear and classes are fun to attend. Nice work Jon. — Brian Griner, PhD on June 5, 2020
Jon gave a truly spectacular presentation on creating deep learning neural networks using TensorFlow. Jon's tutorial was well-oriented to an audience with technical skill but only passing familiarity with NNs. It was accessible, well-structured, well-paced, and inspirational. Despite the limited time, all of us were able to accomplish something foundational. — Barton Poulson on July 11, 2019
Deep Learning for Natural Language Processing video tutorials (23 reviews: 5.0 out of 5 stars)
Dr Krohn does an excellent job of getting you up and functional on the application of theory in a practical way. I was able to easily apply these concepts in real-world problems with a reasonably decent understanding of what I was doing. — Jas Anderson on August 26, 2019
Very well-explained. Love his style of teaching. — Bonson Sebastian Manpilli on February 4, 2019
Extremely practical! — Itay Kaufman on January 23, 2019
Another very good tutorial. Excellent introduction to word vectors. — Thilo Gotz on January 23, 2019
Very informative and this tutorial has a lot of useful references for further reading. The blog post is also very helpful. The codebase is nicely commented and a good place to start from. — Abhir J. on December 31, 2018
I finished watching your first videos on TensorFlow for beginners a week ago and now I'm watching your NLP videos! They are great. Before your videos I had no idea how it works, and now I understand what I should do! I should also mention that the Word2Vec method never been explained better by anyone else! — Ramin Saljoughi Nejad on August 27, 2018
Awesome sessions!!!! — Sumana Pal on June 6, 2018
Helped me a lot with my bachelor [degree] thesis! — Paul Da Wiese on April 3, 2018
This is a really good course. — Jaya Krishna on March 18, 2018
Excellent delivery and content! — student on March 18, 2018
Great course!!! — student on December 18, 2017
Enjoyed going through the NLP series. Very well structured and clearly presented. Many thanks and looking forward to new ones. — Aliya Ibragimova on December 8, 2017
Another excellent series of lectures on state of the art practices in deep learning, geared toward NLP. Dr. Jon Krohn has a gift for explaining complex concepts extremely well, backing up the theory with concrete examples using Keras. Really hoping there is more to come. Many thanks Dr. Krohn! — Basab Dattaray on November 20, 2017
Deep Reinforcement Learning and GANs video tutorials (15 reviews: 5.0 out of 5 stars)
Great. — Rangel Alvarado on December 31, 2018
Amazing instructor, love his tutorials. — Kim on June 13, 2018
Learnt a lot from this amazing course! Thanks. — Siddarth Jain on May 13, 2018
Very good and clear explanations. I wish this course was longer. — Thanos on March 24, 2018
These videos contain the clearest explanation on the intuition behind GANs... Enjoyed the detailed coverage on Deep Q-Learning. — student on February 23, 2018