This blog is started as a way to keep track of my progress in Deep Learning and Natural Language Processing. The entire blog contains explanation and the code for various topics in the above mentioned fields. I intend to make this a place to gather all these concepts so that I can retain them.
Having said all that, I also want this blog to be a place where people can learn these ‘Seemingly intimidating’ topics in Deep Learning and realize that it is nothing but calculus+probability. My personal way of learning is ‘to learn the fundamentals first’ which implies trying not to use libraries from sci-kit learn and API’s like TensorFlow. Accomplishing Deep Learning (or even Logistic Regression) task without Sci-Kit Learn (Logistic Regression()) seems to be a daunting task, but that is where the fun begins. I encourage everyone to follow this way of learning and I can assure you that, you will be amazed to see your progress.
One might wonder ‘Where do I (the author) learn from?’ and that is a very good question. I try and gather resources from various online resources (coursera, udemy, EdX, and some other free online platforms). Recently, I came across the entire Deep Learning and Artificial Intelligence catalogue by ‘The LazyProgrammer’ and I love it. I personally think the way ‘Lazy programmer’ (I would love to know his actual name) explains the concepts is the best it can get. I am currently following his set of courses and major part of my code will be inspired from his GitHub repository (I shall try and incorporate code from other sources as well).
P.S. This blog, is in no way, intended to pirate the resources present in Udemy. In fact I encourage people to take the courses mentioned in this blog because I feel they are the best to learn DL. My goal is to nurture my understanding on these concepts because “ The best way to learn is to teach”.
References for later parts of this blog:
- https://lazyprogrammer.me/
- https://github.com/lazyprogrammer
- https://www.coursera.org/specializations/deep-learning
