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coursera_machine_learning

Programming Assignments of Machine Learning algorithms: Supervised Learning (Linear Regression, Logistic Regression, Neural Networks, Support Vector Machines), Unsupervised Learning (K-Means Clustering, Principal Components Analysis, Dimensional Reduction, Recommendation System), Machine Learning Advice (Bias/Variance Diagnosis, Regularization, Hyper-parameter Tuning), Anomaly Detection.

covid19_data_exploration

Use SQL Server and Power BI to explore global COVID 19 data.

credit_card_fraud_detection

Implement machine learning models which are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.

customer_personality_analysis

Customer personality analysis helps a business to modify its product based on its target customers from different types of customer segments.

data_augmentation

Data Augmentation using Python and OpenCV

fashion_color_classification

Build a model that classifies product fashion but also predicts product color at the same time.

google_image_scraping

Download image from google

image-segmentation

neural_network_coding

Building a deep neural network and apply to image classification problem.

python_useful_mini_projects

This is some useful mini projects that I had worked for self-learning Python programming.

sales_insights

Sales insights data analysis using Power BI and SQL

studying

Studying DA

thinhuos0913.github.io

tweet-emotion-recognition

Build a recurrent neural network and train it on a tweet emotion dataset to learn to recognize emotions in tweets.

uber_lyft_price_prediction

This is a very interesting project, this dataset contains a lot of NA values and many features to do exploratory analysis task. It's good if you use machine learning to build predictive models for Uber/Lyft price prediction