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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.google_image_scraping
Download image from googlefashion_color_classification
Build a model that classifies product fashion but also predicts product color at the same time.data_augmentation
Data Augmentation using Python and OpenCVsales_insights
Sales insights data analysis using Power BI and SQLtweet-emotion-recognition
Build a recurrent neural network and train it on a tweet emotion dataset to learn to recognize emotions in tweets.image-segmentation
python_useful_mini_projects
This is some useful mini projects that I had worked for self-learning Python programming.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 predictioncredit_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.neural_network_coding
Building a deep neural network and apply to image classification problem.customer_personality_analysis
Customer personality analysis helps a business to modify its product based on its target customers from different types of customer segments.covid19_data_exploration
Use SQL Server and Power BI to explore global COVID 19 data.Love Open Source and this site? Check out how you can help us