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Brain-Tumor-Classification-with-Efficient-Net-and-Grad-CAM-Visualization

Brain Tumor Classification with Efficient Net Convolutional Neural Network (CNNs)

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Twitter-Sentiment-Analysis-with-Deep-Learning-using-BERT

Twitter Sentiment Analysis with Deep Learning using BERT and Hugging Face

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Generate-CryptoPunks-with-DCGAN

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Explainable-AI-Scene-Classification-and-GradCam-Visualization

We will build and train a Deep Convolutional Neural Network (CNN) with Residual Blocks to detect the type of scenery in an image. In addition, we will also use a technique known as Gradient-Weighted Class Activation Mapping (Grad-CAM) to visualize the regions of the inputs and help us explain how our CNN models think and make decision.

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Portfolio_Project_Multivariate_Linear_Regression_King_County_Housing

Real estate value prediction using multivariate regression models

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Facial-Expression-Recognition-with-Convolutional-Neural-Network-Grad-CAM-and-OpenCV

Build and train a convolutional neural network (CNN) in Keras from scratch to recognize to predict 7 types of facial expressions (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral)

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COVID-19-mRNA-Vaccine-Degradation-Prediction

Build Bi-directional GRU to predict the degradation rates at each base of an RNA molecule which can be useful to develop models and design rules for RNA degradation to accelerate mRNA vaccine research and deliver a refrigerator-stable vaccine against SARS-CoV-2, the virus behind COVID-19.

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Portfolio_Project_NLP_Show_US_The_Data

Identify how scientific data are referenced in publications using Natural Language Processing (NLP)

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Data_Science_Module-1

Data Science Bootcamp Labs and Projects

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Data_Science_Module-2

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Fake-News-Detection

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Generate-Synthetic-Images-with-DCGANs-in-Keras

We will build and train a Deep Convolutional Generative Adversarial Network (DCGAN) to generate images of fashionable clothes.

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Data_Science_Module_3

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Bitcoin-Price-Prediction-using-Facebook-Prophet

In this work, we will approach the forecast of daily closing price series of the Bitcoin cryptocurrency using data on prices of prior years (January 2016 to August 2020).

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Anomaly-Detection-via-PyCaret

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Build-a-Data-Science-Web-App-with-Streamlit-and-Python

Python

3D-SARS-CoV-2-Protein-Visualization-With-Biopython

We will use Biopython to handle biological sequence data stored in FASTA & PDB (Protein Data Bank) and XML format. Using this sequence data, we will explore and create an interactive three-dimensional (3D) representation of SARS-CoV-2 (Coronavirus) protein structures.

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Portfolio_Project_Image_Classification_Chest_X-ray_Pneumonia

Chest X-rays image classification for early Pneumonia detection using deep neural networks

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Emotion-AI-Facial-Key-points-Detection-with-Deep-Learning-Residual-Convolutional-Neural-Network

In this project, we will build, train and test a Convolutional Neural Networks with Residual Blocks to predict facial key point coordinates from facial images.

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Cervical-Cancer-Prediction-with-H2O-AutoML

In this project, we will identify the characteristics of women who are more likely to develop cervical cancer and use Automatic Machine Learning H2O AutoML to make prediction on whether or not a certain customer would buy a term deposit. We will also use Explainable AI (XAI) methods such as Variable Importance Plot, Partial Dependence Plot, SHAP Summary Plot, and LIME to explain how each of our feature input affects our model prediction.

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Quora-Insincere-Questions-Classification-with-NLP-Transfer-Learning-Using-TensorFlow-Hub

We are going to improve the quality of discussions on Quora platform by detecting toxic content. Specifically, we want to build a predictive NLP model that labels questions asked on Quora as either sincere or insincere.

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Predict-Future-Product-Prices-Using-Facebook-Prophet

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Dognition

Customer-Market-Segmentation

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Movies-Recommendation-with-Similarity-Based-Recommendation-System

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Predict-Car-Price-with-PySpark-MLlib

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Tweet-Emotion-Recognition

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Wikipedia-Toxic-Comments-Classification-with-CNN

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Music-Recommender-System-with-ASL

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Sentiment-Analysis-of-Amazon-Product-Reviews-in-the-Cloud-with-AWS

Employee-Turnover-Prediction

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Image-Denoising-Using-AutoEncoders-in-Keras

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Real-time-OCR-and-Text-Detection-with-Tensorflow-OpenCV-and-Tesseract

A-B-Test-For-Ad-Campaign

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Portfolio_Project_Ternary_Classification_Tanzanian_Water_Crisis

Water point functionality prediction using binary classification models

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Diabetes-Diagnosis-using-Support-Vector-Machines

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Named-Entity-Recognition-using-LSTMs

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Understanding_DeepFake_with_Keras

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Iris-Classification-with-PCA

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Compare-Time-Series-Predictions-of-COVID-19-Deaths

In this project we will create time series analysis models to predict the number of daily deaths due to SARS-CoV-19, or COVID-19 using the following models: SARIMAX, Facebook Prophet, XGBoost, and Neural Network. We will perform predictions using these trained models and compare the accuracy of predictions of these models statistically and visually.

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Bank-Term-Deposit-Marketing-Strategy-with-Automatic-Machine-Learning-H2OAutoML

Identify the characteristics of customers who more likely to respond and commit to a term deposit and use Automatic Machine Learning H2O AutoML to make prediction on whether or not a certain customer would buy a term deposit.

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Life-Expectancy-Prediction-with-H2O-AutoML

We will leverage population's information on immunization, mortality, social- economic and other health related factors and use Automatic Machine Learning H2O AutoML to make prediction on life expectancy of a certain population. We will also use Variable Importance Plot, Partial Dependence Plot, and SHAP Summary Plot to explain how each of our feature input affects our model prediction.

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baotramduong/Data_Science_Module-4

baotramduong

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