martinchavez

Leveraging company data I drive AI and ML-based insights and analyses for informed decision-making. Crime Record Dashboard using Power BI, Python, Sql, Machine Learning. Police Traffic Information System using C#, MS SQL Sever, .NET, Power BI, Python, ML, django. Human Resource Managment System (HRMS) using Python, Power BI, ML, AI Algorithm Optimization: Applied hyperparameter tuning techniques to optimize model performance. Deep Learning: Developed and trained deep neural networks (CNNs, RNNs, LSTMs) for tasks such as image recognition, natural language processing (NLP), and time-series forecasting. Deployment: Deployed machine learning models into production environments using Docker and Kubernetes, ensuring scalability and reliability. Model Evaluation: Assessed model performance using metrics such as precision, recall, F1 score, and ROC AUC, and improved results through cross-validation and model stacking.

Model Development: Designed and implemented machine learning models for predictive analytics, classification, regression, and clustering tasks using Python, TensorFlow, and PyTorch. Data Preprocessing: Processed and cleaned large datasets, performing feature engineering, normalization, and dimensionality reduction to improve model accuracy. Cloud Services: Utilized cloud platforms (AWS, GCP, Azure) to develop and deploy machine learning pipelines, leveraging tools like SageMaker, BigQuery, and Databricks.

Data Analysis: Conducted deep-dive analysis on large datasets, uncovering trends, anomalies, and insights to drive business decisions. Data Visualization: Created detailed dashboards using tools such as Tableau and Power BI to present data-driven insights to non-technical stakeholders. SQL Expertise: Wrote complex queries to extract and analyze data from relational databases (MySQL, PostgreSQL), ensuring data accuracy and integrity. Predictive Analytics: Utilized machine learning models and statistical tools like Python and R to forecast business outcomes and improve operational efficiency. Collaboration: Worked closely with cross-functional teams, including marketing, sales, and finance, to translate data insights into actionable strategies. Data Cleaning: Implemented data cleansing techniques to ensure datasets were accurate and prepared for analysis, reducing errors by 14%. Reporting: Automated weekly and monthly reports using Excel, reducing time spent on manual reporting by 25%.

Designed and implemented scalable database architectures for various applications using technologies such as MySQL, PostgreSQL, and SQL Server. Developed complex SQL queries, stored procedures, and triggers to retrieve, manipulate, and maintain data efficiently. Improved query performance by indexing, optimizing joins, and analyzing query execution plans, resulting in a X% reduction in query response times. Managed backup, restoration, and disaster recovery processes to ensure the high availability and security of critical business data. Developed ETL processes to efficiently transfer and transform large datasets between different systems, ensuring data consistency and accuracy.