Hi!
I'm Soheil

I'm a Data Scientist and Python Developer

I have been an M.Sc. student in the field of computer engineering and the subfield of artificial intelligence and robotics at Azad University since 2020. Currently, I'm working on my thesis. Throughout my academic years, I worked for an insurance brokerage company.
I'm very passionate about machine learning and deep learning, especially NLP, so I've been participating in Coursera, Data Camp, and Dayche courses. I worked on machine learning projects and used Python during my classes.
Currently, I'm looking for a job in data science or python developer. I always enjoy dealing with challenging problems and finding new ways.

HARD SKILLS

  • Expert in:

    Machine Learning, Deep Learning, Python, Scikit-Learn, Numpy, Pandas, Matplotlib, Seaborn, Keras

  • Intermediate in:

    Transfer Learning, Git, Linux, SQL, Web Scraping, API

  • Basic in:

    Transformers, Pyspark, Pytorch, Tensorflow, Pycaret, Streamlit, Gradio, Hadoop Ecosystem, MongoDB, Django, Fast API, Docker, Power BI, HTML, CSS

SOFT SKILLS

  • Problem Solving, Teamwork, Communication, Creativity, Eager to Learn

EDUCATION

Sep 2020 - Present

Azad University (TNB)

M.Sc. in Artificial Intelligence and Robotics

  • GPA: 18.42/20
  • Thesis Topic: Camouflage Object Detection (working on it)

Sep 2018 - July 2020

Azad University (TNB)

B.S. in Software Engineering

  • GPA: 17.68/20
  • Final Project: Market Basket Analysis

Jan 2016 - Jan 2018

Applied Science and Technology (Iranian Informatics)

A.S. in Computer programming

  • GPA: 16.03/20

EXPERIENCE

Jan 2023 - Present

Cando Training Center

Instructor

  • Courses:
  • Python Foundation MasterClass

Feb 2023 - Present

Adorateb

Regional Sales Expert

  • Data Gathering from QlikView
  • Data analysis using excel
  • Increase sales performance by providing hints to sales supervisors and managers

Aug 2020 - Apr 2022

Tamin Ayandeh Insurance Broker

Head of the Department of Issuance of Personal Insurance

  • Data Gathering
  • Preprocessing data
  • Data analysis using excel

Dec 2014 - Aug 2020

Tamin Ayandeh Insurance Broker

Personal Insurance Expert

CERTIFICATE

Data Science

272 hours
December 2021
Dayche
In this course I learned about:
• Data Mining & Problem-Solving Approach
• Applied Statistics & Probability
• Python Programming & Basic Analytics
• Hacking Skills (Linux & Git)
• Working with Data Sources (SQL & API)
• Fundamentals Of Machine Learning
• Machine Learning Implementation in Python
• Special Topics in Data Science (NLP & Deep Learning)
• Big Data Analytics in Spark

ICDL

12 hours
May 2019
Cando

PROJECTS

  • Market Basket Analysis

    January 2020 Bachelor Degree Final Project Technologies: python, pandas, matplotlib, mlxtend

    In this project, a review was made on association rules discovery methods and implement Apriori algorithm on market basket dataset.

  • Students Status in Final Examination (Passed or Failed)

    June 2020 Practice Project Technologies: python, numpy, pandas, matplotlib, sklearn

    This project is defined as a binary classification. The task was predicting students' status in the final examination (passed or failed). The dataset is available in the UCI machine learning repository. First, define this project as a binary classification problem by summing three scores. After preprocessing the data (get dummies), train the model using the decision tree classifier algorithm. In the inference phase, I achieved 69% accuracy.

  • Anomaly Detection on Credit Card Dataset (Fraud Detection)

    January 2022 Master Degree Advanced Data Mining Course Final Project Technologies: python, pandas, matplotlib, seaborn, scipy, sklearn, keras

    Imbalanced classification is the main challenge of this dataset. The dataset includes transactions made on credit cards in September 2013 by European cardholders and was published in Kaggle as a competition. In this project, dimension reduction techniques like PCA and Autoencoder were implemented. In order to extract classification rules, I implemented Decision Tree and Naïve Bayes algorithms, which were evaluated with ROC AUC and achieved 98% and 96%.

  • RFM Analysis

    December 2021 Dayche Data Science Class Project Technologies: python, numpy, pandas

    The main goal of this project was customer segmentation considered by their loyalty. Calculating Recency, Frequency, Monetary of customer transactions makes this purpose possible.

  • Predict Apple Stock Price (Time Series)

    December 2021 Dayche Data Science Class Project Technologies: python, numpy, pandas, matplotlib, keras

    In this project, predict the open price in the daily timeframe of Apple stocks with LSTM (Long short-term memory). First, with ACF, see autocorrelation to find the best lag time. After that, create a 60-day lag and then model with LSTM. This model can predict the trend of price, but not exactly price.

  • Personal Blog

    October 2022 Practice Project Technologies: python, django, HTML, Bootstrap

    This is a simple Django project. I create a blog app and define URLs, models, templates, admin page. In this app, you can share a post with the admin page. For a front-end side, I used HTML and Bootstrap.

  • Linear Regression

    May 2022 Practice Project Technologies: python, numpy, pandas, matplotlib, seaborn, sklearn

    I implement linear regression from scratch in three different types (univariate and IID, multivariate and IID, and multivariate and non-IID) using Python and NumPy. 

  • Iris Classification Web App

    August 2022 Practice Project Technologies: python, pandas, streamlit, sklearn

    Iris is a well-known machine learning dataset. In this app, I create a web app with Streamlit and predict the type of iris flower. 

  • Cat Classification

    September 2022 Practice Project (Coursera exercise) Technologies: python, numpy

    The primary goal of this project is to classify cat and non-cat images. I implemented a neural network in order to assign labels to images. The model accuracy in the test set was 80% after evaluation.

  • Neural Network

    May 2022 Practice Project (Coursera exercise) Technologies: python, numpy

    I implement neural network from scratch, including forward and backward propagation, using Python and NumPy.

CONTACT