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Operationalizing machine learning models with GCP VertexAI
In today's data-driven world, operationalizing machine learning (ML) models efficiently is crucial for organizations aiming to derive...
Deploy ML models with Docker
In recent years, Docker has revolutionized the way software applications are deployed and managed, including machine learning (ML)...
Deploy ML models with Flask
As discussed in the previous project, Flask is another valuable API for deploying models. Let's delve into deployment with Flask! From...
Deploy ML models with FastAPI
Building an ML model is an essential step, but it’s not the end of the journey. In real-world applications, the model needs to be...
Techniques for tuning classification models with imbalanced dataset
When working on classification models, we usually found that our data have a difference number of members among each classes, some...
Rating Prediction of AirBNB Listing
Imagine you are working with AirBNB and your boss wants to know popularity of listings, so they could have insights to setup proper...
EPL Ranking with Bayesian Inference
As a football fan, sometimes you might wonder how good your team is compared to other teams, or even thinking about predicting the final...
My GAN Wife
Sometime you may wonder how does your 2nd wife look like, but you do not have that chance, then you just learn about GAN, so, why don’t...
Seam Carving Algorithm and its Implementations
Seam Carving is one of the most versatile algorithm for image resizing, it finds the path of pixels on the picture having the lowest...
GridSearchCV versus RandomizedSearchCV
In any machine learning problem, we usually need to perform hyperparameter optimization to tune parameters in our model. Even though...
Precision-Recall curve versus ROC curve for imbalanced datasets
In Binary Classification, we usually use the ROC curve to evaluate performance of our model, but sometimes it will be misleading...
Neural Network and its Applications
Neural network is one prominent machine learning algorithm nowadays, it has been widely used in many applications such as image detection...
Common Mistakes in SQL
As a data scientist or a data analyst, we usually need to work with SQL when we need to pull data from SQL servers or to combine and...
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