Hamed Mehrabi

😊Hey There! Glad to see you here. These are some of the ML/DL projects that I made during my AI learning journey.

Hi, I'm Hamed Mehrabi, a passionate machine learning engineer. I am constantly improving my knowledge to stay up-to-date with the latest developments in the field of data science. I have over three years of experience in data science, and I have a track record of successfully implementing data science pipelines in production. I have practical expertise in using MLOps, deep learning, and machine learning techniques.

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My technical skills

Here is a list of technical skills and tools that I have employed in my Machine Learning projects.

  • Operating System: Windows, Linux
  • Programming Language: Python, SQL, C#.
  • ML frameworks&libraries: Tensorflow, Keras, PyTorch, PyG, Scikit-learn, Pandas, Numpy, Matplotlib/Seaborn, NPL/NLTK
  • MLOps tools: Mlflow, Linux, GIT, DVC, Docker, Kubernetes, TFX, Kubeflow, Jenkins, Elasticsearch, Kibana, FastAPI, Flask, Ansible, Terraform, Featureform, BentoML
  • Cloud skills: GCP(GCP Vertex Ai, Bigquery), AWS
  • Business development skills: Feasibility study, Market research, Business model design

My Portfolio

Here you can find some of my Machine Learning and Deep Learning projects. The scope of these projects encompasses various aspects of machine learning such as predictive modeling, computer vision, and natural language processing. Each project is a complete end-to-end solution, incorporating modeling, deployment, and MLOps.

MLOps Project: Drug Discovery - Binary Classification

This ML project aimed to predict the permeability of compounds in PAMPA assay using their SMILES strings for binary classification. 18 algorithms, including traditional ML and GNN-ML frameworks like PyG and DeepPurpose, were evaluated using standard metrics. An accurate model was developed to guide drug discovery and development, and an end-to-end ML architecture was created, incorporating model training, testing, and operationalization. Technologies used included Python, shell scripting, AWS, Prometheus, Grafana, FastAPI, S3 bucket, and Jenkins for CI-CD. Endpoint monitoring and infrastructure were included for the ADMET_PAMPA_NCATS dataset.

CNN Project: 101 foods classification using DVC

The project is an end-to-end multiclass classification problem that categorizes images of food into 101 classes using a VGG-16 architecture (CNN). The project has been implemented using TensorFlow Pipeline and DVC (Data Version Control). The codes used in this project follow standard Object-Oriented Programming (OOP) principles, ensuring consistency and maintainability.

mlflow- NLP Project: Binary Classification using Microservices Architecture for StackOverflow Tag Prediction.

The project is a natural language processing (NLP) binary classifier problem of predicting tags for a given StackOverflow question. For example, we want one classifier which can predict a post that is about the R language by tagging it R. The project uses MLflow for tracking our experiments, and it is built on a microservices architecture, making it an end-to-end project. The dataset can be downloaded from this link.

My Certificates

Here you can see some of my credentials and certificates in the field of Machine Learning and Deep Learning.