I have just finished uploading a new video course about Hyperledger Fabric and Composer – First Practical Blockchain.
I made this course because I see many people talking about Bitcoin and blockchains but they don’t really know how the tech works! It’s all just a buzz word and that would hamper the true potential of the technology. So, here’s a brief course that will help you understand how Crypto Currencies (such as Bitcoin) work and get you started with your first blockchain and smart contract using Hyperledger Fabric — one of the most popular, modular frameworks for blockchains.
So, head over to the link above and get your intro in 1.5 hours.
I have a new video course that helps aspiring computer scientists excel in almost any area that they decide to pursue by teaching them about the Linux command line — one of the best investments in time anyone working with computers can make.
The course is for beginners but even has something for people who’ve had a little prior experience with the command line.
For my blog readers, I’m making it available for just $9.99 (with a 30-day money back guarantee). Use the following link to get your discount: Linux Command Line – From Zero to Expert
Once you know about the command line, you will be in a position to learn much more interesting stuff such as Linux system administration, VoIP and many more.
I’ve just finished creating a new video course on Udemy about Practical Deep Learning with Keras and Python. It’s aimed at two types of people:
- Those who are just coming to machine learning and deep learning and want a soft (code-based introduction) as opposed to the mathematical treatment typically given to the subject.
- Those who have had ML/DL before but have trouble applying the concepts in code.
For the dedicated readers of my blog, I’m making it available at the minimum price of just $9.99. Please use the following coupon link to access it at this price.
If you want to receive updates about content uploads, coupons and promotions, please subscribe to my mailing list here on mailchimp.
Update: If you are interested in getting a running start to machine learning and deep learning, I have created a course that I’m offering to my dedicated readers for just $9.99. Practical Deep Learning with Keras and Python .
So you’ve been working on Machine Learning and Deep Learning and have realized that it’s a slow process that requires a lot of compute power. Power that is not very affordable. Fear not! We have a way of using a playground for running our experiments on Google’s GPU machines for free. In this little how-to, I will share a link with you that you can copy to your Google Drive and use it to run your own experiments.
BTW, if you would like to receive updates when I post similar content, please signup below:
First, sign in to an account that has access to Google Drive (this would typically be any Google/Gmail account). Then, click on this link over here that has my playground document and follow the instructions below to get your own private copy.Read More »
Update: If you are interested in getting a running start to machine learning and deep learning, I have created a course that I’m offering to my dedicated readers for just $9.99. Practical Deep Learning with Keras and Python.
I gave a talk on Practical Machine Learning, which was well received. It covers the concepts from absolute scratch and covers all prerequisites. It also covers the theoretical foundations. Please go through the videos and let me know how I can improve them.
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Part 02 wasn’t recorded but you can start with 03 without it.
So, I’ve been teaching CS101 – Introduction to Computing this semester (Fall 2017). We picked Python as the language. I’ve compiled the videos and all the lecture notebooks. These are being made available in the hopes that they can be useful for someone. Here’s how to get started with these. Read More »
Protein function prediction is taking information about a protein (such as its amino acid sequence, 2D and 3D structure etc.) and trying to predict which functions it will exhibit. This has implications in several areas of bioinformatics and affects how drugs are created and diseases are studied. This is typically an intensive task requiring inputs from biologists and computer experts alike and annotating newly found proteins requires empirical as well as computational results.
We, here at FAST NU, recently came up with a unique method (dubbed DeepSeq — since it’s based on Deep Learning and works on protein sequences!) for predicting functions of proteins using only the amino acid sequences. This is the information that is the first bit we get when a new protein is found and is thus readily available. (Other pieces require a lot more effort.)
We have successfully applied DeepSeq to predict protein function from sequences alone without requiring any input from domain experts. The paper isn’t peer reviewed yet but we have made the paper available as preprint and our full code on github so you can review it yourself.
We believe DeepSeq is going to be a breakthrough inshaallah in the field of bioinformatics and how function prediction is done. Let’s see if I can come up with an update about this in a year after the paper has been read a few times by domain experts and we have a detailed peer review.