In this post, I’d like to talk about predicting a pattern of a stock price.
Generally, there are two methodologies for predicting a stock price.
One is fundamental analysis, which focuses on analyzing the financial statements of a company. Although those financial statements and indices from it are important and relevant for predicting its price, it isn’t always an answer for it.
It’s because the numbers in financial statements such as sales and profit can be easily manipulated by the company in its favor. Also, there exist many things that cannot be represented in financial statements.
For example, sometimes you can observe…
Previous posts can be found in the links below.
In this post, I’d like to talk about the natural language processing that I implemented in my project.
At the beginning of the project, what I was planning to build was a feature that suggests names of listed companies related to each news article and predicts whether the news has a positive or negative effect on its stock price.
The first thing I came up with was using deep learning to do natural language processing with news articles. However, after a lot of trial and error, I found it was much…
The previous post can be found in the link below.
Since I explained about developing a scraper with Scrapy in the earlier post, let’s see how to deploy it with a Telegram bot.
Telegram officially supports bot API for developers. It works as below.
Telegram bot is located between a user and a developer passing the input from a user to a developer. Then, with the input from a user, the developer can execute any application in the back-end and return the results to…
If you already have Telegram installed, you can just add news_bot by typing @info_scraper_bot in telegram’s search bar to add it.
The server is on 24/7 and free for 7days. Since I’m a Korean, the news bot is scraping news and announcements of Korea and supports only Korean.
Key features are as follows.
This project is available to anyone. You can try it on the website linked above.
Don’t take it seriously! The model may produce an unreasonable result since it has been trained with only 500 face images of Koreans who are in their 20s and 30s.
I started this project last September, and it took about 3weeks to finish. To practice development and deployment with what I learned from Coursera, I started the project with the topic related to image processing.
In the beginning, I got a couple of ideas, including diagnosing hair loss with images of the forehead and…
I started the machine learning course with thoughts of ‘Let’s just test my English skills.’, ‘I’m a business student, so I would be satisfied even with learning just some of them.’ However, as I gradually improved, I found machine learning was not only for a genius. Even for students with a non-technical major, it was possible to understand if you have a little bit of mathematical knowledge from high school, though it took some time for me to get used to vector calculation. At this point, studying machine learning from Coursera became more important than my real school work. …
It has been almost a year that I’ve been studying data science. It feels like I finally get the hang of it, thanks to several projects I’ve been doing so far. However, the meaning of data science sounds too broad and ambiguous, so I want to help you understand what it is at first. …