My personal website developed by using HTML, CSS and JavaScript. As a programmer and magician, I need two separate websites for two kinds of audiences, but I also need to integrate these two websites together. It's a simple static website, but I developed this website by myself. A lot of skills are required to build this website.
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This is the process of how I implemented a linear regression algorithm from scratch, how I created the coefficient function, and how I created the R-square function. You may wonder why I didn't just import the algorithm from scikit-learn directly. The main reason is that as a data scientist, you not only need to know how to implement a model, but also you have to know the algorithm inside of your model so that you can create a better model.
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his is the process of how I implemented a K-Nearest Neighbors algorithm from scratch. K-Nearest Neighbors is one of the most popular machine learning models. To understand how it really works, I implemented the algorithm from scratch. In the end, I compared my KNN model to sklearn’s KNN model. The accuracies are almost the same.
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Since I’m very interested in the self-driving car industry, I used Python to create a Convolution Neural Networks (CNN) model to simulate a self-driving car. It’s very similar to the ongoing self-driving experiments conducted by Tesla, Google, Uber, and so on. My process is simpler, but the idea is the same.
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SQL is commonly used by data analysts and data scientists. I had used different types of SQL, such as SAS proc SQL, PopSql, MySQL Workbench, MS SQL. In the end, I decided to use Amazon Redshift. This is an example of how I use Redshift. It's very intuitive. I just loaded the data from my AWS S3 bucket by using IAM role method.
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