Machine Learning in the Browser, you better not do any lunges!
Let’s demystify for dummies
Machine Learning is a concept which allows the machine to learn from examples and experience, and that too without being explicitly programmed. So instead of you writing the code, what you do is you feed data to the generic algorithm, and the algorithm/ machine builds the logic based on the given data.
Have you ever shopped online? So while checking for a product, did you noticed when it recommends for a product similar to what you are looking for? or did you noticed “the person bought this product also bought this” combination of products. How are they doing this recommendation? This is machine learning. Of course this is a very vulgar example of how complex machine learning is really .
Let’s loop this from an engineer perspective:
AI (Artificial intelligence) is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
ML (Machine learning) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task.
Currently, the most famous deep learning library in this is Google’s TensorFlow. To give a concrete example, Google users can experience a faster and more refined the search with AI. If the user types a keyword a in the search bar, Google provides a recommendation about what could be the next word. This is again a tiny example of what you could witness from deep learning.
TensorFlow was built to run on multiple CPUs or GPUs and even mobile operating systems, and it has several wrappers in several languages like Python, C++ or Java. It was first made public in late 2015, while the first stable version appeared in 2017. It is open source under Apache Open Source license. You can use it, modify it and redistribute the modified version for a fee without paying anything to Google. More deeply speaking, A tensor is a vector or matrix of n-dimensions that represents all types of data. A tensor can be originated from the input data or the result of a computation. In TensorFlow, all the operations are conducted inside a graph.The graph is a set of computation that takes place successively.
Tensorflow can be run on many different platforms. You can run it on :
- Desktop running Windows, macOS or Linux
- Cloud as a web service
- Mobile devices like iOS and Android
You can train it on multiple machines then you can run it on a different machine, once you have the trained model.
The subject is vast, it means that there is width, but if you consider the depth, each topic can be learned in a few hours. Each topic is independent of each other. You need to take into consideration one topic at a time, learn it, practice it and implement the algorithm/s in it using a language choice of yours. This is the best way to start your way in Machine Learning.
“The only limit to AI is human imagination.” ― Chris Duffey
Special Thanks to Abderrahim Soubai Elidrissi for this great « Human » Learning moment.