Unofficial but extremely useful Label and One Hot encoders.
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Updated
May 1, 2021 - Python
Unofficial but extremely useful Label and One Hot encoders.
Classification task using supervised learning techniques algorithms: k-NN & decision trees
Exercises for the "Data Analytics" course, University of Bologna (2021/2022)
📶In this repository, we will do feature engineering with Python.
Flask API serving a trained ML model to perform inferences over the input Json.
Basic ML Algorithm that uses advanced regression techniques to predict the price of a house
Classification of Sentinel-2 land cover multiband images through an ensamble of DNN
Digit Recognition Neural Network: Built from scratch using only NumPy. Optimised version includes HOG feature extraction. Third version utilises prebuilt ML libraries.
The primary goal of this project is to convert free users of a financial tracking app into paid members. This conversion will be achieved by building a model that identifies users who are unlikely to enroll in the paid version of the app.
Binary classification algorithm that predicts which passengers are transported to an alternate dimension
A two layered LSTM model to solve binary classification problem (positive and negative movie review)
Neural Network using NumPy, V1: Built from scratch. V2: Optimised with hyperparameter search.
A comparison of a few sample optimization algorithms has been made using the IRIS dataset on Keras and Sklearn frameworks.
One-hot encoding for simple molecular-input line-entry system (SMILES) strings
Create a machine learning model using logistic regression that can predict credit card approvals from the described dataset.
When Will We Arrive? A Novel Multi-Task Spatio-Temporal Attention Network Based on Individual Preference for Estimating Travel Time
Korean OCR Model Design(한글 OCR 모델 설계)
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