Predict a price of 1BDR apartment in New York City based on Trulia, Yelp and demographic data.

Predictive model for solar energy consumption. An exploration of residential solar energy consumption as a time series. Use of ML models trained interactively with a selection of duration for the training window period.

Example for studying statsmodels

A simple linear regression machine learning model for predicting the total cases of pandemic from OWID dataset. Built using Python libraries (Pandas, NumPy, Statsmodels, Pickle, Matplotlib, Seaborn). Model is further represented as a Flask Web Application with a backend database connectivity to SQLite3 using SQLAlchemy. Later deployed to Heroku …

Time Series concepts and code snippets.

Boston House Price Prediction using multivariable regression.

Predicting economic recession in developed and developing countries using regime-switching model

Generate forecasts using several time series forecasting models

Test various time-series Models to predict future movements in the value of the Japanese yen versus the U.S. dollar.

Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States. Assume Null Hypothesis as Ho is p1-p2 = 0 i.e. p1 ≠ p2. Thus Alternate Hypthesis as Ha is p1 = p2. Explanation of bernoulli Binomial RV: np.random.binomial(n=1,p,size) Suppose you perform an experiment with two possible outcomes: either success or failure. Success happens with pro…

Exploring and predicting the price of cars based on their features

Tool demonstrating time series decomposition

For this Project, I first applied an analysis of variance (ANOVA) model to the Pymaceutical dataset and then did a post-hoc analysis of the results by using Tukey Honest Significant Difference (HSD) to determine which drug treatments in the dataset significantly reduce tumor volume and metastasis. I then wrote a summary of my findings.

Assorted ML exercises from various sources

Time series analysis for Templehof-Berlin using historical data of daily temperature.

Data Science: Statistical Tests with Python

OpenClassrooms Data Analyst 2022-2023 - Projet 10

Algorithmic Trading in Python

Deriving actionable insights to inform strategic decision-making for a fictional SaaS company's sales operations.

Analyzing O3 Air Quality Index trends (2000-2023) in the U.S., this project identifies regions with rising pollution. Utilizing exploratory data analysis and time-series modeling, it offers actionable insights for informed policy decisions on urgent O3 pollution issues.