I think I mentioned earlier that Guido van Rossum, the author of Python joined Microsoft! Turns out we are almost neighbors in sunny California, so after exchanging a few e-mails with Guido: it’s an honor to sign the book on AI with Python to the original author of Python language! I hope we can work together on bringing Python to Microsoft products and services!
Thanks #Python community for all your enthusiastic support of my book and course on AI in Sports with Python! During the last 3 months that it was published, I received a tremendous support from the community, more than two hundred people supported the project on Kickstarter, and the book is being translated to other languages.
I’m also very happy that Guido van Rossum, the creator of Python joined Microsoft! As an author of AI with Python book and course, I learned a lot about the ecosystem and the language and I love it! Many partners and startups I work with share the excitement, so looking forward to working with Guido!
I decided that retirement was boring and have joined the Developer Division at Microsoft. To do what? Too many options to say! But it’ll make using Python better for sure (and not just on Windows :-). There’s lots of open source here. Watch this space.— Guido van Rossum (@gvanrossum) November 12, 2020
I walked past a very impressive Halloween Castle, someone in our community put together, with whispering witches and skeletons the size of a two story house, and watching kids coming to watch, play and talk to scary and spooky characters, I couldn’t avoid a temptation to think about a Halloween Special for Data Scientists, something to impress trick-or-treaters even more. I immediately thought that quite a few examples in my book qualify for Halloween special!
Speaking of spooky bones and skeletons: in Chapter 3 of my book and video course there’s a fun example of segmentation methods for tissues, bones and MRI detection. I used an MRI scan of my own knee to demonstrate some of the tools a data scientist can use in radiology. Segmentation is important in many areas of computer vision, and the example of using Scikit-image and OpenCV to segment areas on MRI scans.
Of course there’s much more AI examples for Halloween we can apply to impress kids even more! Robotics is the key part of animating those scary characters in front of your gate greeting trick-or-treaters. Reinforcement learning can be applied to animate humanoid models. Applying AI is certainly fun, and Halloween can get even better!
AI already helps scoring sporting events, like gymnastics in the upcoming Olympics, thanks to systems like Fujitsu’s for example. Sports science traditionally applied biomechanics for sports analysis, and it works really well! AI can help this traditional approach by adding methods from supervised, unsupervised and reinforcement learning.
Supervised learning can help with labeled sets of data in tasks like classification, for example classifying sports activities:
Unsupervised learning doesn’t assume that data is labeled, instead its goal is finding similarities in the data. It’s often used for self-organizing dimensionality reduction and clustering. For example, if you train an unsupervised model with sufficient data containing images of athletes performing actions in different sports, such a model should be able to predict what group, or sport a given image belongs to.
Reinforcement learning (RL) applies a concept of an agent trying to achieve the goal and receiving a reward for most positive actions. There’re some really cool applications of this method in sports that I covered in my book.
Want to learn more on applying ML in sports? Check out my book and the course that covers a lot of material with detailed walk throughs.
This is my 24/7 virtual book signing page: you can get your signed book anytime, by clicking the button at the end of this post. If you already have my book or video course “AI in Sports with Python”, click here to Get an Electronic Signature! Or if you would like to have a physical copy of the new book with my signature on it click Get a Paperback Book with Signature ($5 flat rate shipping anywhere in the US/Canada only)!
Ever wondered how your author signed book is getting shipped? I have the process now completely streamlined, so if you want to support the book and (a vague hint) my next book, you can get a signed copy fast!
Thanks to my publishers, Apress, I have a stock of books ready and waiting for signature 🙂
I ship with Stamps.com, your book will be shipped with USPS mail service in the US. The book weighs about 1 lb 6 oz and fits very nicely in a box from Amazon.
The label is printed on my trusty laser printer and your book is shipped via US Postal Service. This is my virtual signing and shipping process at the moment. Have fun and enjoy!
Some of the oldest datasets on human motion and sports comes from ancient images, sculptures and paintings. Scenes depicted in cave art took place 30,000 years ago, and sculptures from ancient Olympics and can still be analyzed today with deep vision methods and used to train our models. Think of the longevity of information preserved in these sculptures and images!
I allocated several chapters on deep vision methods in my book: from basics of neural nets, to 2D and 3D pose estimation, video classification and more.
Video announcing my book “Applied Machine Learning for Health and Fitness”
Announcing LIVE cast on Linkedin with Kevin Ashley, hosted by Mike Downey and APRESS, discussing AI in Sports technology with examples from Kevin’s book “Applied Machine Learning for Health and Fitness” and the video course “AI in Sports with Python” based on the book.
WHEN: 9/17 THURSDAY AT 2PM Pacific Time (PST)
WHERE: LinkedIn – Mike Downey will be hosting LiveCast, click on his profile at 2PM and join the livecast!
Post #AISportBook and the name of your favorite #Sport plus the photo of the sport on Linkedin, Twitter or Instagram to win:
- 5 books “Applied Machine Learning for Health and Fitness”
- Access to “AI in Sports with Python” video course
After counting, winners will be drawn! This will also help me understand your interest in sports in the future episodes of my “AI in Sports with Python” online course!
“AI in Sports with Python” (Deep dive online course)
It’s for anyone interested in sports, artificial intelligence, and new applications for sports and fitness. Learn to apply AI in sports with Python with fun applications in many sports: tennis, surfing, skiing, snowboarding, skateboarding, football, gymnastics, basketball, javelin, weightlifting, track and field and much more!
Want to learn more? Check my new course, that complements the book!
The course is accompanied by practical step-by-step Python code samples and Jupyter notebooks. These models and methods can be used to create solutions for AI enhanced coaching, judging, athletic performance improvement, movement analysis, simulations, in sports, health and fitness, motion capture, gaming, cinema production and more.