Basic Machine Learning implementation with python
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Updated
Jul 1, 2020 - Jupyter Notebook
Basic Machine Learning implementation with python
Predicting gender of given Chinese names (93~99% test set accuracy). 预测中文姓名的性别(93~99%的测试集准确率)。
Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value
Multi class and Binary Classification through Logistic Regression and SVM
The projects are part of the graduate-level course CSE-574 : Introduction to Machine Learning [Spring 2019 @ UB_SUNY] . . . Course Instructor : Mingchen Gao (https://cse.buffalo.edu/~mgao8/)
Implementation and analysis of core Machine Learning Algorithms from scratch.
Image Classification, Image Feature Extraction, CNNs, Finetuning, Resnet18, Torchvision, Multi-Class Logistic Regression
Using classic machine learning models - K-NN, Multiclass Logistic Regression, SVM and Random Forest to make predictions
Investigated how multi-class logistic regression would perform if the activation function was changed from softmax to sigmoid. It included mathematical analysis and empirical evaluation, such as rewriting the model from scratch. Tech: Python (scikit-learn, pandas)
Multiclass logistic regression implementation from scratch
An NLP model that can predict the probability for each type of toxicity of comments.
Implementation of Trust Region and Gradient Descent methods for Multinomial Regression
Employee Task management and review system for EinNell Expound Hackathon 2019
💵Model Peruvian Bills (MLR, Mask, Inceptionv2) RCNN💶
We investigated the performance of the Logistic and Multiclass Regression models and compared their accuracies to KNN. We compared Logistic Regression and KNN based on the "IMdB reviews" dataset, while Multiclass Regression and KNN were compared based on the "20 news groups" dataset.
Logistic Regression is a supervised learning algorithm that is used when the target variable is categorical. In Logistic Regression the target variable is categorical where we have to strict the range of predicted values. Consider a classification problem, where we need to classify whether an email is a spam or not. So we have to predict either …
This is the term project for the Mathematical Foundations of Data Science course in Bilkent University. The aim of this project is to automatically diagnose skin cancer from images.
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