Open jasonwee opened 4 years ago
slide 2 the executive summary of your solution
With the ever changing of human lifestyle due to rise of information technologies, our life fill with not just a lot of data, different type of data, speed of data reaching us, different of medium data reach us. It is easy to feel lost in such a digital world.
One of data which is interesting is digital cryptocurrencies. With different cryptocurries available and amount of data its generated every minute, to determine at what particular point of time to buy or sell is a difficult decision. Sure, there are professional who can trade efficiently using their experience, but given the technologies emergence such as machine learning and big data analytics, we think there are many interesting areas where technologies can decide better than human at the tips of user view.
slide 3
General diagram
+-----------+ +----------------------------------+
| ML | /| messari crypto provider |
| processor|\ / +----------------------------------+
+-----------+ \ /
\ / +----------------------------------+
+--------------+ /| coingecko crypto provider |
| |/ +----------------------------------+
| crypto system| ..
| | ..
| | +----------------------------------+
| |--| NNN crypto provider |
+--------------+ +----------------------------------+
slide 4
Our system aim to give a simple yet intuitive alerts recommendation to user. This is achieve by integrating with various digital currencies providers by ingesting various data sources and turn this data into a useful information. We will use machine learning technologies from amazon sagemaker to turn different data we collected from multiple source providers into useful information and the score will alert to the user when to buy and sell.
If our project idea is of interested by the judges, given time and resources, we will like to integrate to exchange such that user can actually enter the market to trade. Our crypto system can also integrate to newsfeed such as twitter or facebook and interesting keyword should influence our ML processor recommendation, thereby increase further the recomendation confidence. Now we will use mysql for initial proof of prototype, our ultimate goal is move to cassandra and elasticsearch
slide 5 A working demo video (optional: code repository)
slide 1 the experiences & skills of all the team members
slide 2 the executive summary of your solution
slide 3 the executive summary of your solution
slide 4 the executive summary of your solution
slide 5 A working demo video (optional: code repository)