I work with Python, R and SQL to prepare, explore and visualize data, and develop predictive models. My interests include deep learning, distributed data processing and practical problem solving, check out 👇🏼
"The genius's brand is clarity, the failure's brand is confusion" - Brian Tracy
- Data preparation: collection, cleaning, transformation and filtering.
- Data analysis and visualization with Python and R.
- Supervised learning: regression and classification.
- Unsupervised learning: clustering.
- Time-series analysis and forecasting.
- Database querying and analysis with SQL Server.
- Driving Data Science, Machine Learning and Deep Learning with Python, R and now I will be driving Scala tech principles!!
- Database analysis with SQL Server.
- Scripts development and implementation in automated supervised learning models (Regressions, Classifications and time series) and unsupervised (Clustering) with Programming languages such as Python and R.
- Modeling mean libraries: Pandas, NumPy, Matplotlib, Scikit-Learn, Seaborn, Keras, TensorFlow, dplyr, ggplot2, readr, VIM, lifecycle, lubridate, etc..
- Data Analysis through collection, transformation, filtering and cleaning with Jupyter Notebook and Databricks.
- Structured databases and file formats like:: structured books, flat files, AVRO, Parquet, JSON and ORC formats.
- Connection string with Apache Hadoop (HDFS for store, YARN for resources and MapReduce for processing).
- Essential touch development with SCALA.
- Learning Azure Machine Learning, with Data Factory and Synapse Analytics.
- Curious about AI + Problem Solving.
