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Data scientist, developer of predictive
models using machine learning and deep
learning techniques with Python, Scikit
learn and Tensorflow, specialized in
regression problems, binary and multiple
classification, computer vision and NLP.

Zero To Mastery Academy

Universidad Nacional Experimental Politécnica

Data Scientist & Machine learning Engineer

Joel Calanche

Freelance

Deep Learning Engineer

NLP project.
Developer an 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 model, different embedding forms(multi data models).

Computer vision project
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.


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 a time series data. Exploratory data analysis ,data cleaning, feature engineering, model selection, evaluation
metrics and feature importance.

Machine Learning Engineer 

Developer of a logistic regression model with Scikit-learn for binary classification of patients with heart diseases, based
on previous medical records. EDA, model selection, feature importance, metrics evaluation (ROC curve and AUC score,
confussion matrix, accuracy, recall and f1 with cross validation).

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