Posts

LLM series Post 1: What is a LLM ?

 A lot of people might have known what a LLM is at this point. Most people call it a large language model. But i call it an autoregressive multi class classifier because the functionality of an LLM is to predict the next word and move on until it encounters the end of the sentence. In the series of post i am going to explore what an LLM is and how it is trained and what are the industry terms like "prompt engineering", "one shot" prompting, other buzz words are in terms of Machine learning.  This post is written by me and may not be that fluent because i did not ran it through a large language model because i find it counter intuitive to write a LLM post by using LLM. I am not a person who is supporting or against LLM because with correct mindset and usage i think it can be very useful. Although a lot of people write a lot of articles about LLM. in general, i find everything to be same that is lacking depth or blocked by paywalls so i am writing what i understand a...
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Who this blog is for ?

This is a classic post that I always like to write because it tells the reader what they need on a technical level to read my blog. Everyone is welcome to expand their knowledge and skills, but the problem is if you don't have a background in Computer Science and Machine learning / Data Science then this blog will be very hard for you to understand. I do not intend to write it in a complex way but the topics that I write are complex. If you do not want complex topics, please visit my technology blog because it will explore latest technologies ( I like to call them as tech trends). Technologies that I like to discuss in my posts: 1. Compilers and Low-level stuff 2. Operating systems and operating system level stuff 3. Machine learning and artificial intelligence. The posts that i write are based on the research that i do. Please email me if you find any errors so that i can edit it. I don't check my writing with LLM so it might contain continuity errors or grammatical errors. I ...
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Post freqency and update

When i created this blog i thought i would be writing a blog every other day but when i had commitments I left blogging. I thought of returning to blogging ever since the day i left. As soon as i left blogging i saw a explosion in AI technologies like GPT and image generation models and there were a lot of blogs popping up in medium and other sites with information about AI and data science. Because of all the blogs that popped up i thought to not to blog because it was not worth the effort. But after 4 years, in the internet everything i see is either AI generated or AI corrected or manipulated in some way. I don't know whether it is but i feel it is because of the shallow knowledge everything provides. I am having a masters in Data science and in my work i design programs that train AI models with large data sets. I also know that everyone does not need deep knowledge but a simple introduction, but what i feel is the information should be available for the one who needs it. So i ...
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Deriving the positive and negative factors from hotel reviews using NLP

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Data driven decision making is an art of making decisions and improvements on business using data analysis. Today data is collected in every means possible. For example, the duration taken by you to read this article is a data. This article discusses about the data driven decision making in the scenario of hotel administration. The hotel which has high positive reviews is a good place to stay, and these reviews also hold multiple factors that contributes the success of a hotel. Nowadays, hotel businesses depend on the star rating which determines their popularity among the users. The star rating will give only general idea about the popularity, but it will not specify the factors (services that is provided by the hotel). In the recent times, we have a powerful method based on Natural language processing. By harnessing this we can determine what are factors that contribute to a good review for the hotel. As discussed above, reviews contain multiple information. If a hotel has good q...
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