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advanced-ai-transformers-for-computer-vision-3085710

This repo is for the Linkedin Learning course: Advanced AI: Transformers for Computer Vision

ai

breastcancerclassifier

cancer-burden-vs-rcb-visualization

Python script to visualize predicted cancer burden vs. RCB values. Uses matplotlib, numpy for plotting, and sklearn for accuracy calculation. Scatter plot groups data based on cancer burden predictions, and regression analysis assesses the relationship. Shadi Momtahen

cnn_classification

Deep learning project using TensorFlow to classify images of flowers from the "Flowers Recognition" dataset, which is an open-access dataset available on Kaggle: https://www.kaggle.com/alxmamaev/flowers-recognition

cnn_cvm_lr_braintumor_cassification

This project employs CNN, Logistic Regression, and SVM to classify brain tumors into distinct classes. Emphasizing accuracy and loss metrics, it provides a succinct evaluation of model performance. Standardized preprocessing ensures efficient training, and visualizations depict training accuracy and loss over epochs.

cnn_image_classification

Image Classification with CNN

computervision_transformer_detection_segmentation_classification

In this project, we explore various ML techniques for brain tumor classification, including Random Forest, Logistic Regression, CNNs, VGG16, Transfer Learning, GANs, and Computer Vision with BERT.

cross-validated_estimator

Cross-validated estimator to enhance the regression analysis

deep-learning-sentiment-analysis

This project performs sentiment analysis on movie reviews using a deep learning model (LSTM) to classify them as positive or negative.

deeplearning-cnn-fcnn-logisticregression

A deep learning classifier for males/females classification

dl_classification

Deep learning networks for classifications, with different architectures of Neural Networks and their configurations.

ecgsignalprocessing

ensemble-learning-absorption

This repository contains a Python script for medical absorption prediction using ensemble learning. It preprocesses data, applies KNN-based Bagging Regressor, and generates visualizations. Ideal for researchers. Author: Shadi Momtahen. Scikit-learn, Pandas, Matplotlib referenced

former

Simple transformer implementation from scratch in pytorch.

gans_generative-adversarial-networks

genai__stablediffusion_text-to-image-app

genai_llm_tranformer_gradio_app_gpt_bert

gr

gradient_descent_regression

Gradient Descent for Regression

gradientboosting

image-classification-cifar10

A machine learning project showcasing image classification using a CNN model on the CIFAR-10 dataset. Demonstrates proficiency in Python, TensorFlow, and deep learning techniques.

infection-prediction-cnn-randomforest

Explore predictive healthcare analytics with this Python code. Utilizing Random Forest and CNN models, it analyzes COVID-19 infection data, showcasing preprocessing, training, and evaluation. A practical example for leveraging ML in biomedical data analysis for disease prediction.

large-language-model-llm-

llm_nlp_sentiment_analysis_flask_app_docker_deployment_kubernetes

logistic_regression

The objective of this work is implementation of a pairwise classifier for two digits using regularized logistic regression classifier with a ridge (L2) regularization via mini-batch gradient descent.

logisticregression_gradientdescent

Implementation of Logistic Regression via Gradient Descent (GD), using 9 features, and predict heart disease which has 2 classes (0 and 1).

mesh_open3d_pointcloud

mlclassification_signalprocessing

multi-class_classification_softmax

Multi-class Classification using SoftMax Regression