As an experienced Data Scientist, I am focused on enhancing energy systems through data-driven methods. I am an expert in managing large datasets, effective data cleansing, and advanced statistical analysis. I develop predictive machine learning models to forecast energy trends and support strategic decisions.

Core Competencies:

• Data Management: Competent in managing large-scale data sources, ensuring data integrity and accessibility.

• Data Cleansing and Transformation: Skilled in improving data quality by correcting inaccuracies and inconsistencies.

• Statistical Analysis: Expert in analyzing complex datasets and identifying significant patterns.

• Machine Learning Development: Proficient in creating predictive models using the latest techniques to improve operational efficiency and trend predictions.

• Data Visualization and Reporting: Talented in creating visuals and reports that effectively communicate data findings.

• Continuous Improvement (CI/CD): Committed to the continuous updating and maintaining the effectiveness of models and processes.

• Time Series Analysis: In-depth knowledge and experience in using time series data to analyze and predict solar energy production and consumption trends.

As a seasoned Data Scientist and AI Engineer, I am actively involved in mentoring and educating aspiring data professionals. My mentorship and training program covers a comprehensive range of topics in the field of Data Science and Machine Learning. Here's an overview of the key areas I focus on:

• Python Programming: Fundamental to advanced concepts in Python, tailored for data science applications.
• CRM Analytics: Techniques and insights for analyzing customer data, improving customer relationships and driving business growth.
• Measurement Problems in Data Science: Tackling common challenges in data measurement and ensuring data integrity.
• Recommendation Systems: Developing systems to suggest products or services to users based on their preferences and historical data.
• Feature Engineering: Techniques for creating and selecting impactful features to improve the performance of machine learning models.
• Machine Learning: Comprehensive understanding of various machine learning algorithms, from basic to advanced, including supervised and unsupervised learning.

This program is designed to empower participants with practical skills and in-depth knowledge, equipping them to excel in the rapidly evolving field of Data Science. For more information or to participate in my training sessions, feel free to contact me.

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• Banking Risk Asssesment with ML

• Customer Churn Analysis with Machine Learning

• Telco Churn EDA,Feauture Engineering and Modeling

• Diabetes Feature Engineering

• A/B Test_Averages_of_Two_Different_Groups

• Rating Product & Sorting Reviews in Amazon

• FLO Customer Lifetime Value Prediction BG/NBD Gamma Gamma Models

• FLO Customer Segmentation with RFM Analysis

• Rule-Based-Segmentation

• Predicting Service Request Loads using LSTM model with Keras

• Predicting Stock Prices Using RNN Model

• Prediction with 7-Classification Models | ROC AUC

• K-Means Clustering : Customer Segmentation - Bonus : RFM

• Salary Prediction with Regression and CART Model

• Diabetes Prediction & Feature Engineeringl

• Telco Churn Prediction with Machine Learning Models (%80 Accuracy)l

• Association Rule Learning Recommender

• Video Title Sorting Reviews and Measurements [EDA]

• Customer Segmentation with RFM Analysis

• Exploring Data Analysis on the Titanic Dataset

• Team Goal and Expected Goal Performance Analysis

• Comparing Milan vs Inter teams using Visualization

• Machine Learning and Modeling Stroke Data

• Visualization-Prediction Analysis Turkey - Update

• Covid-19 Countries Visualization & Analysis-Update

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