Currently a Full-stack Java Developer at Brillio Technologies building scalable applications in Springboot and React.

Siddhant Bhardwaj  • Peerlist

In this project, I attempted to predict the trading volume of the Bitcoin cryptocurrency from December 2014 to September 2019. I applied recurrent neural network method to predict the trading volume and visualized the results.

Prediction of Bitcoin Trading Volume

In this project, I have attempted to classify mushrooms into poisonous or safe categories. I have applied multiple classification algorithms and achieved maximum accuracy of 95.8%

Classification of mushrooms as poisonous or safe

In this project, I attempted to predict the housing prices for homes in King County, Washington State, USA sold between May 2014  and May 2015.  I performed exploratory data analysis and data visualization exercise on the dataset and applie

Housing Price Prediction (King County, Washington)

Created a computer vision model for people with visual impairment to help navigate to a desired location. Model is able to     detect up to 80 different obstructions with 98% accuracy in the path of the user along the route. Route specifica

Third Eye

In this project, I analyzed the MNIST digit recognition database consisting of 70,000 handwritten digits.  The project aimed at applying machine learning techniques to recognize the handwritten digits from 0 to 9. The project applied classi

Handwritten Digit Recognition

In this project, I have attempted to classify individuals as to whether or not they are diabetic. The project analyzes the impact of multiple lifestyle choices on an individual's health with respect to their being diabetic. I have used mult

Predicting Presence of Diabetes

In this project, I performed a time series analysis of the daily electricity production from December 1984 to December 2017. I checked if the time series was stationary and used the ARIMA method and the LSTM method in order to perform the a

Time Series Analysis of Daily Electricity Production

This project aimed at predicting the price of diamonds on the basis of multiple features like carat, cut, quality and color. The dataset used consists of 54,000 samples. I have applied multiple regression algorithms to predict the diamond p

Diamond Price Prediction

In this project, I attempted to predict the national happiness scores of  multiple countries based on rankings of multiple categories of well-being like GDP per capita, family, health, trust in the government etc. The dataset used comes fro

Predicting Happiness Scores from World Happiness Report (Gallup Poll)

In this project, I performed a time series analysis of the monthly beer production from December 1955 to December 1985. I checked if the time series was stationary and used the ARIMA method and the LSTM method in order to perform the analys

Time Series Analysis of Monthly Beer Production in Australia

This project aimed to predict the personalized medical costs of an individual based on multiple factors such as sex , BMI  ,number of children , smoking habits and region. The project applied multiple regression algorithms like Linear Regre