Gold Price Prediction

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  The Workflow of our project is depicted as Flow Chart

Inspiration

• As a consumer we've always fascinated by the ever changing prices of gold, hence we wanted to develop a solution to predict the market and understand how it works.

What it does

• Our project factors past gold prices and market changes to predict the future changes to help investors.

How we built it

• We built our solutions with various ML algorithms such as Long Short Term Memory(LSTM) and Random Forest Regression models. We have also used a dataset containing current gold prices. We trained the model in google colab and we deployed it in IBM Z PLATFORM using Jupyter Notebook.

Challenges we ran into

• The data set had different currency values and we had to adjust our model according to it.
• We also had to clean the dataset to our desired format.

Accomplishments that we're proud of

• Since our project is applicable for daily purposes, we are proud that we've contributed to the community.
• Our model also has atmost accuracy to the trend of prices.

What we learned

• We managed to learn importance of data quality.
• We also got an idea of differnt ML algorithms and how they work.
• Our team also got an idea of how mainframes work and the process of setting up on through Z PLATFORM.

What's next for Gold Price Prediction

• We are planning to expand our research to various other materials (Platinum etc.).
• We are also hoping to launch a AI tool to assist investors.

Built With

• ibmz
• python
• tensorflow