Arman Ahmed
About Arman Ahmed
SUMMARY : - 2+ years of experience in developing and deploying machine learning and deep learning algorithms into production for various data-driven problems involving regression, clustering, anomaly detection, classification, time series forecasting, active learning, and cybersecurity. - Ph.D. graduate student focusing on the applications of machine learning and deep learning algorithms to solve real-world problems. Completed Masters (MS) and a Bachelors (BS) degree with a computer science major. - Highly Proficient in Python, R, TensorFlow, Keras, PyTorch, NumPy, Pandas, Scikit-Learn, Matplotlib, and have a solid understanding of Algorithms, Data Structures, and Object-Oriented Programming. - Have extensive analytical skills and a significant ability to work in a team environment. - Adept at collecting, analyzing, and interpreting large datasets using statistics, developing predictive models delivering insights to implement action-oriented impactful solutions. - Experienced in distributed machine learning (synchronous and asynchronous data parallelism). - Experienced in Git, GitHub, Docker, Microsoft Azure, Google Cloud, and Amazon Web Services (AWS). - Hands-on experience with Data Engineering experience in ETL (Extract Transform Load) using PySpark, Pig, MapReduce, Spark, Hadoop, Jupyter Notebook, Cassandra, Zeppelin, HBase, Hive, Kafka, MLlib, SQL, MySQL, SQLite, PostgreSQL, and NoSQL (MongoDB). SKILLS : Programming Language : Python, Java, R, C++, C#, and Matlab. Data Science : Statistical Analysis, Data Cleaning, Exploratory Data Analysis (EDA), Data Visualization, Hypothesis, and Significance Testing. Machine Learning : Linear Regression, Logistic Regression, Support Vector Machines (SVM), Decision Tree, Random Forest, Naive Bayes, K-Nearest Neighbors (KNN), K-Means, Random Forest, Principal Component Analysis (PCA), and Ensemble Learning (Bagging and Boosting). Deep Learning : Convolutional Neural Network (CNN), Long Short Term Memory Network (LSTM), Autoencoder, Encoder-Decoder, Anomaly Detection, and Time-Series Forecasting. Data Engineering : PySpark, Hadoop, Spark, Airflow, Jupyter Notebook, Cassandra, Zeppelin, HBase, Hive, Kafka, MLlib, SQL, MySQL, SQLite, PostgreSQL, and NoSQL (MongoDB, MongoDB Atlas). Tools : Keras, Pandas, NumPy, Git, GitHub, Microsoft Azure, Google Cloud, Pig, MapReduce, Amazon Web Services (AWS), PyTorch, PyTorch Geometric, TensorFlow, Scikit-learn, Stats-Model, Matplotlib, HBase, Hive, Kafka, Spark, and MLlib. Reach me at : armanahmedrzi@gmail.com