The ML / AI Project Litecoin Inference

I had the privilege of working among some of the most intelligent people I have ever known for several years while I was head of IT and DevOps at Skytree (The machine learning company) back in 2013-2016, way before the AI LLM hype that has taken over the world.

 I learned from and worked with giants in the industry. Some of them went on to build their own companies, and some are legends in the field. While there, I got a real-world education in ML and what it could do at scales that hadn't been tried before. 

 In my off hours, I took Coursera courses on ML and the R Programing languages classes. After about the second year, I knew enough about our product and ML in general that I often stood in the booth, gave presentations about our product to passers-by at conferences, and sat in as a sales engineer at client meetings.  

Now the problem: While at Skytree, I talked to a colleague about ML and inference. With enough candle stick technical analysis stock data (a method many day traders use), I wanted to know if I could predict stock prices. I wanted to see if we couldn't automate using our ML / AI technology to make those predictions. I was told the company's founder did such a thing and made and lost a million dollars in a year. I was told a lot of the stock market is based on emotional and public perception, making it a complex problem to solve. 

  Fast forward years later, and as an amateur data scientist, I wondered how NLP sentiment analysis models of news and events, plus candle stick patterns of stock, might create an excellent model to make price predictions. (Solving the stock market, how naive I was). For the source of news and sentiment, I turned to Twitter and selected a target to watch: the cryptocurrency Litecoin. 

Come along on a journey as I level up my ML / AI skills to include CNN with Tensorflow and collect and capture data to try to predict the future of Litecoin. 



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