I'm a data scientist with over a years of experience in the field. My expertise lies in using statistical analysis and machine learning techniques to solve complex business problems.

• Python
• Statistical analysis
• Machine learning (supervised and unsupervised learning)
• Deep learning
• Data visualization and storytelling

Here are some of my recent projects that showcase my skills and expertise:

This project is a machine learning application that predicts the quality of red wines based on their physicochemical properties. The dataset used for this task is the Red Wine Quality dataset from the UCI Machine Learning Repository. The main goal of this project is to train a classification model that can accurately predict the quality of red wines based on their physicochemical properties. To achieve this goal, we used a Random Forest classifier, which is an ensemble learning method that combines multiple decision trees to improve the accuracy and robustness of the predictions.Check out the repository for more information.

This project explores the relationship between various measurements of fish and their weight, with the goal of building a linear regression model to accurately estimate the weight of a fish based on its measurements. The dataset used for this project includes measurements of several fish species, including their length, height, width, and weight. Check out the repository for more information.

This project aims to classify five different types of rice - Arborio, Basmati, Ipsala, Jasmine and Karacadag - using the MobileNet model. With an accuracy of 99%, our model can accurately classify the rice types based on their unique features.Check out the repository for more information.

This project uses the YOLOv8 model to detect Harry Potter, Ron Weasley, and Hermione Granger in movies. We trained the model on a custom dataset of Harry Potter movie frames. . Check out the repository for more information.

This project uses deep learning techniques to classify images of cats and dogs. I built a Convolutional Neural Network (CNN) model that achieved an accuracy of over 90% on the test set. Check out the repository for more information.

TThis project uses a Deep Convolutional Generative Adversarial Network (DCGAN) to generate anime faces. DCGAN is a type of generative model that can learn to generate realistic images by training on a large dataset of images.Check out the repository for more information.

• Google Data Analytics from Coursera And Google

Gain in-demand skills for an entry-level job in data analytics with Google's professional certificate, designed to prepare you for a career in the high-growth field of data analytics.

• IBM Data Science from Coursera And IBM

This Professional Certificate from IBM on Coursera is designed to help anyone interested in pursuing a career in data science or machine learning develop the skills and tools necessary to succeed in the field.

• Machine Learning Specialization from Coursera

The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach the fundamentals of machine learning and how to use these techniques to build real-world AI applications.

• Deep Learning Specialization from Coursera

The Deep Learning Specialization is a foundational program that will help understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.

I'm always looking to connect with other data scientists and professionals in the field. You can find me on LinkedIn or reach out to me via email.