Joel Calanche

Python developer & Machine Learning Engineer

  Portugal, Olhao

Phone : +351-913163772

Phone: +351-924701160

email : [email protected]

Python developer and Machine learning engineer , developer of predictive models using machine learning and deep Learning techniques with Python, Scikitlearn and Tensorflow . Specialized in regression , binary and multiple class
classification problem, Computer vision and NLP. With knowledge about deployment and Mlops following the protocol 329S: Machine Learning Systems Design of Stanford University .

Experienced working with  structure and unstructured data,  scripts, data scraping, handling APIs, automation and testing with selenium, micro web services with flask ,streamlit and django. Server developer, database administrator with postgreSQL.  With solid knowledge of data structure, graphs and algorithms.

Project Portfolio:

Machine learning Skills

  • Tensorflow2.0                                       
  • Keras
  • Python 3
  • Scikit-Learn
  • Pandas
  • NumPy
  • Jupyter Notebook
  • Flask
  • Selenium
  • Docker
  • streamlit
  • Django
  • Matplotlib
  • SQL
  • Time Series Forecasting

Data Engineer Skills

  • Kafka
  • Hadoop
  • Azure Data lake
  • Amazon S3
  • Spark
  • Flink
  • Spark Streaming
  • Kineses


  • Spanish — Native
  • English — Profesional

I A Projects &  Applications

Deep Learning  

NLP project: "SKIMlLIT"
Developer of a NLP model to classify abstract sentences into the role they play (e.g. objective, methods, results, etc) to enable researchers to skim through the literature (hence SkimLit ) and dive deeper when necessary. Feature engineering is used; hybrid models, different embedding forms(multi data models).  A f1 score of 0.79 was reached in test dataset.

september 2021 - october 2021

Deep Learning 

Computer vision project: "FOOD VISION"
Developer of a model based on convolutional neural networks with Tensorflow that allows identifying between 101 different classes of food dishes, using EffcientNet (transfer-learning) and new mixed precision features of tensorflow. 75,750 images (750 per class) were used for the training set and 25,250 (250 per class) images for the test set, an accuracy of 0.80 was reached  in test dataset .

may 2021 - august 2021

Machine Learning  


Developer of a predictive random forest regression model with Scikit-learn and Python to estimate the cost of sales of heavy machinery(bulldozer), based on time series data. Exploratory data analysis ,data cleaning, feature engineering, model selection, evaluation metrics and feature importance. The data is from the Kaggle Bluebook for Bulldozers competition. A r square value of 0.87 was achieved  in test dataset .

march 2021 - april 2021

Machine Learning

 Heart disease detection (binary classification project)

Developer of a logistic regression model with Scikit-learn for binary classification of patients with heart diseases, based on previous medical récords(14 different medical features). EDA, model selection, feature importance, metrics evaluation: ROC curve and AUC score, confusion matrix, accuracy, recall and f1 with cross validation. the model achieved a value of f1 of 0.88  in test dataset .

january 2021 - febrary2021


Zero To Mastery Academy

Tensorflow developer

2021 - 2021

Zero To Mastery Academy

Machine Learning , Data Science

2021 - 2021

Universidad Nacional Experimental Politécnica

Bs in Electrical Engineering

2013 - 2019

Powered by CakeResumePowered by CakeResume