Bernad Biju

I'm a dedicated learner with experience in Python. I'm excited to apply my skills to real-world projects.

• weather-temp-predict

I used scikit-learn linear regression model to predict weather, Collected real-time data of the weather using OpenWeather API, Used StandardScaler to improve accuracy, Explored possible improvements but currently facing problems due to small dataset and other limitations.

• note-organizer

I used scikit-learn logistic regression model to predict what the notes based on keywords, then used the   LabelEncoder and TfidfVectorizer for data preprocessing.

• stock predict

I used XGBoost model to predict if Googl's stock price went up or down (when the market closes), based on news and previous patterns in the stock. I leveraged the NewsAPI to pull news, then turned it into a positive or negative value using sentimentintensityanalyzer, merged them, and used the 5-fold training method to train the model, which had 79% accuracy. This accuracy is really bad, but when compared with the amount of data (1 month)and it's an early project, it's somewhat reasonable, I believe.

• data collection on sales in a game

 I used an API that pulls data of the sales of item real time. I used this API to make a tool that adds this data to my csv file every 60 sec.

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