Stanford - The Natural Language Processing Course


Long time ago, when the first courses about natural language procession and machine learning had released, I was planning to get them. I announced around and let people know what they could have, what they couldn’t. In short, I was excited. But years were passing and I couldn’t have attend because of short of time and being very busy.

A few weeks ago I was contemplating about tf-idf. I looked for it and read some pages and continued to search, eventually run across the nlp course. I watched the related videos, since then I’ve been continuing.

Learning something for need is much better than learning to fill spare time.

Comments

Post a Comment

Popular posts from this blog

Migrating from PHP to Python

At last, I’ve made a strong decision to migrate from PHP to Python. Leaving a tool, leaving your bread basket would not be an easy decision if you used it almost for eight years. Otherwise, I believe that sometimes with a little bit courage to leave your conform zone and a lot of curiosity you can get a better bread basket, maybe a jar of jam too. if you want to be a sea, you must give up being a drop. Why am I leaving PHP? Actually I am not leaving PHP totally, but switching my primary language to Python because my works have been changing. Most of work required from me is related to natural language processing(NLP), machine learning(ML) techniques. And I, and many other developers, find Python much more capable to deal with this kind of works. It has already many libraries, tools, frameworks for NLP and ML. Another reason is that I think web programming will not grow as much as an intelligent system. Maybe I am wrong, but there is no doubt the future is about intelligent systems.
Read more

Memory organization and cache management

Image
In computer systems, caches are used to diminish the slowness of main memory which is larger and cheaper than cache memory. Caches are faster because not far from CPU and not as large as main memory. In modern computers, there may be more than one cache memory. The layers composed a memory hierarchy. The memory hierarchy is sometimes called an illusion to processors because a processor can have as large and fast a memory as it needs at the level of reasonable cost. In short, from a broader perspective it is easy to understand why memory hierarchies are needed; however, to understand how it works you need to narrow the perspective, e.g. taking account only two memory layers at one time. Key concepts are: cache miss and hit ratios. memory and cache and average access speed memory size, cache size block or cache line size set size direct mapping, fully associative mapping, set associative mapping address partitioning (tag bits, index/set bits, block bits) replacement algor
Read more

(DRAFT) Scaling a django project using celery and elasticsearch

Scalability has undoubtedly become an important asset not only for large software projects but also mid-level ones now. Indeed, when you have a look at developer job posts, you can see easily that the need to build scalable software is one of the top desired skills. Making a software scalable requires mostly more than one methodology and different technology stacks. At first, it may look difficult and require deep experience with those methods and stacks. And yes, scalability is a serious topic. Although it is, in this post, I will show how to make a Django application scalable. In the end, you will learn fundamental concepts and approaches. PLAN create a django project which is a little product management system. make adding product asynchronous instead of synchronous sync elasticsearch with the primary database ( SQLite ) use elasticsearch for autocomplete and real-time analysis 1. Product management app with Django Since I assume you are familiar with Python and Dj
Read more