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Series
In this series, I will venture the down a path of development using various languages, mainly Python, and utilise AI for the majority if not all of the code generation.
Is this what a dev does? In this series of articles, I'm going to take you through a little journey that I've decided to label as 'NotADev'. Why, you may ask? Well, I've dabbled in Python scripts for some years whilst doing web2 ethical hacking and r...
![Article = [i for i in NotADev]](https://cdn.hashnode.com/res/hashnode/image/upload/v1727480461686/cbfa04ea-b838-40d3-8bc7-9e25a546a092.png)
Fetching Stock Data with yFinance With the idea in place and my setup ready, it was time to start coding—or, more accurately, instructing AI to code for me. Getting the Data I needed historical stock data. The AI suggested using the yfinance library...
Enriching Data with Technical Indicators With the stock data successfully fetched and initial error handling in place, it was time to delve deeper into the data to make it more informative for our predictive models. The idea was to enrich the data wi...
Introducing Machine Learning Now that the data was enriched with technical indicators and lag features, it was time to build a predictive model to forecast stock movements. 💭 I’ve worked on predictable models for decades, mainly around services, cu...
Advancing the Model with New Features and Overcoming Challenges As I continue my journey to enhance my trading bot, I've reached a significant milestone—the integration of new machine learning features into my model. This has been both an exciting an...
Aligning the Trading Script with the Enhanced Model In the last article, I talked about how I collaborated with ChatGPT to introduce new features to my trading model, such as Recursive Feature Elimination (RFE), XGBoost, and hyperparameter tuning. Wi...
