I am a machine learning engineer and data scientist with a taste for adventure. I love to explore the world of data and find hidden insights that can help businesses grow,with the skill to deploy, monitor, and maintain machine learning models. I am always looking for new ways to use data to make discoveries and create new products and services. I am always looking for ways to collaborate and learn new things from others to achieve great things.
- 💬 Ask me about how I use machine learning to solve real-world problems, end to end projects
Data Preprocessing: NumPy, Pandas
Machine and Deep Learning Implementation Framework: Scikit-Learn, PyTorch, TensorFlow
Natural Language Processing: NLTK, BERT. Development: Python, Git.
Data Visualization: Matplotlib, Seaborn.
Cloud Services: AWS
Integrated Development Environment: Jupyter-Notebook, VSCode, PyCharm.
⚡Experience in developing and implementing machine learning models and algorithms. This includes experience in data preprocessing, feature engineering, model selection, hyperparameter tuning, and model evaluation, including working with different types of machine learning models such as supervised learning, unsupervised learning, and reinforcement learning.
⚡Proficient in object-oriented programming using Python and capable of writing clean and efficient code that is easy to maintain and scale.
⚡Experience in working with machine learning frameworks such as TensorFlow, PyTorch, Keras, Sklearn, and Langchain
⚡experience working with cloud platforms such as AWS. Capable of deploying and managing machine learning models on these platforms efficiently.
⚡Experience working with databases such as SQL and being able to work with different types of databases efficiently to extract data from them for machine learning purposes.
⚡Strong understanding of statistics, mathematics and the ability to apply statistical concepts such as hypothesis testing and regression analysis to solve real-world problems using machine learning.
