Tassawar Abbas

About Me

I am a passionate and results-driven data scientist with a strong background in economics. With a Master's degree in Economics, I bring a unique perspective to the field of data science, combining analytical rigor with a deep understanding of economic principles.

Experience

I have over 5 years of experience working in various data-driven roles, where I have leveraged my expertise to extract actionable insights from complex datasets. My experience spans across industries, including finance, healthcare, and e-commerce, where I have contributed to projects ranging from predictive modeling to business intelligence.

Skills

My skill set encompasses a wide range of tools and techniques relevant to data science, including:

• Data Analysis and Visualization: Proficient in Python and R programming languages, with expertise in libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data manipulation, analysis, and visualization.

• Machine Learning: Experienced in building and deploying machine learning models for classification, regression, and clustering tasks using libraries such as Scikit-learn, TensorFlow, and Keras.

• Statistical Analysis: Strong foundation in statistical methods and hypothesis testing, with proficiency in using statistical tools and techniques to derive meaningful insights from data.

• Data Cleaning and Preprocessing: Skilled in data cleaning, preprocessing, and feature engineering techniques to prepare raw data for analysis and modeling.

• Big Data Technologies: Familiar with big data technologies such as Hadoop, Spark, and Hive for processing and analyzing large-scale datasets.

Projects

1. Customer Churn Prediction

• Description: Developed a predictive model to forecast customer churn for a telecommunications company using logistic regression and random forest algorithms.

• Tools and Libraries: Python, Scikit-learn, Pandas, Matplotlib, Seaborn

2. Image Classification with Convolutional Neural Networks (CNN)

• Description: Built a CNN model to classify images of handwritten digits from the MNIST dataset using TensorFlow and Keras.

• Tools and Libraries: Python, TensorFlow, Keras

3. Sentiment Analysis with Recurrent Neural Networks (RNN)

• Description: Implemented an RNN model for sentiment analysis of movie reviews from the IMDB dataset, achieving state-of-the-art performance in sentiment classification.

• Tools and Libraries: Python, TensorFlow, Keras

Education

• Master's in Economics: [Punjab University], [2007]

• Bachelor's in Economics: [Punjab Univeristy], [2003]

Certifications

• Machine Learning A-Z™: Hands-On Python & R In Data Science

  • Issuing Organization: Udemy
  • Description: This course covers a comprehensive introduction to machine learning algorithms in both Python and R. Topics include supervised and unsupervised learning, regression, classification, clustering, and more.

• Python for Data Science and Machine Learning Bootcamp

  • Issuing Organization: Udemy
  • Description: This bootcamp-style course focuses on Python programming for data science and machine learning. It covers topics such as data analysis, visualization, machine learning algorithms, and real-world projects.

• Deep Learning A-Z™: Hands-On Artificial Neural Networks

  • Issuing Organization: Udemy
  • Description: This course provides a comprehensive introduction to deep learning and artificial neural networks. Topics include neural network architectures, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and more.

Contact Me

Feel free to reach out to me via email at [abbas829@gmail.com].

Let's collaborate and drive impactful data-driven solutions together!