Welcome to my portfolio! I am a passionate and skilled data enthusiast with extensive hands-on practice in Python, SQL, Power BI, MS Excel, and Tableau. Below, you will find an overview of my projects categorized by technology, highlighting my expertise in data analysis, visualization, machine learning, and development.
The project deals with solving the business problem of online grocery delivery chains, Instacrt.The data of 3 million orders by 200000 customers has been analyzed to understand the customers' buying behaviours. K-Means algorithm and Market Basket Analysis have been applied for segmenting the customers based on their buying needss and discover the products association.For predicticg the customer's reordering probability, XGBoost Model and ANN model have been implemented to predict the customer's reordering probability.
In the following machine learning classification problem, the project aims to predict the customers whether they going to be default the loan or not based on the various financial features. The handle the imbalance data the combination of oversampling and undersampling knoen as SMOTEENN have been used. Logistic Regression, Random Forest with its hyperparters and CATBOOST models have been applied to solve the business need.
The main goal of the project is to predict the used car's price based their several features. To solve this machine learning regression problem, numerous data cleaning and feature enginnering approaches have been implentented during data exploration and preprocessing phase.Moreover, I have applied Decison Tree Regressor, Random Forest, XGBoost Model and KNearest Neighbour to attain the best results.
The project involes the comprehensive customer segmentation analysis using clustering techniques and Principal Component Analysis (PCA). The project includes data preprocessing, exploratory data analysis (EDA), hierarchical clustering, K-Means clustering, PCA, and clustering with PCA. Visualizations and model saving are also part of the project.
This repository contains a collection of solutions to various Pandas problems from LeetCode, as an exercise designed to enhance your data manipulation and analysis skills using the Pandas library in Python.
The exercise contains the solution of LeetCode SQL challenges. The aim of the exercise is write the SQL queries from basic to advance to have the hands-on practice for extracting the meanfuls data insights.
The exercise contains the solution of LeetCode SQL challenges. The aim of the exercise is write the SQL queries from basic to advance to have the hands-on practice for extracting the meanfuls data insights.
This repository contains a comprehensive SQL project that manages an employee database. The project includes the following key components including Database Schema Design, Data Insertion,Table Alteration, Data Manipulation, Data Retrieval, Views and various Advanced SQL functions used for analysis.
Developed a comprehensive HR analytics dashboard in Tableau, visualizing key employee metrics and attrition analysis, and provided actionable insights for improving retention and satisfaction strategies.
The interactive dashboard below shows the important data insights from the Netflix dataset. The dashboard shows the count of movies and TV shows, the percentage difference between movies and TV shows, the top 10 genres, and the number of TV shows and movies by year. The data can be filtered by type and movie name.
Tableau for Data Scientists
Power BI Essential Training
SQL: Data Reporting and Analysis
Google Data Analytics Certificate
• Python: Data Visualization (using Matplotlib, Seaborn), Data Transformation and Processing (using NumPy, Pandas), Machine Learning (with scikit-learn), Deep Learning (with TensorFlow, Keras), Statistics (with SciPy) (Intermediate to Advanced)
• SQL: For Data Manipulation, Extraction and Analysis using queries (Intermediate to Advanced)
• MS Excel: For Data Cleaning and Transformation, Data Visualization and Statistical Analysis (pivot tables, Regression, Time series forecasting). (Intermediate)
• Tableau: For Data preparation, Visualisation and Dashboard Creation. (Intermediate)
•Power BI: For Data Modelling and Transformation using DAX and Power Query, Dashboard and Report Creation. (Intermediate to Advanced)
Tableau for Data Scientists
Power BI Essential Training
SQL: Data Reporting and Analysis
Google Data Analytics Certificate
Email: haidermuhammadadfaseeh@gmail.com
LinkedIn: linkedin.com/in/muhammadfhaider