Bike Sharing Dataset This dataset contains the hourly and daily count of rental bikes between years 2011 and 2012 in Capital bike share system with the corresponding weather and seasonal information. I downloaded this dataset from UCI Machine Learning Dataset. Google Colab is fine to run the codes and show the data. Let’s…

Hi everyone, I have been following Medium for a long time, but I have been actively using it for 2 months. I have used Medium for a long time by opening it from the browser incognito tab. …

4. inheritance and subclasses We created our class. But our factory has grown. Our employee profile is slowly changing. This makes it difficult to apply the features in the classroom to all staff. You can think of it like this, taxonomically speaking, humans and mice have common features from the mammalian class, but differ…

1.Decision Trees A decision tree classifier is a supervised learning technique that is used to classifiy the data based on some pivot points. For example, if you can not decide whether to go outside or not so you ask your self “Is it rainy outside?”, “Do i like playing football?”, and “Will I…

As you know, Python is one of the object-oriented programming languages. So what is the object? Roughly speaking, items that have certain methods and/or attributes in Python are called objects. In other words, the word ‘object’ consists of a simple nomenclature, a phrase used to describe items that contain some…

There are various hyperparameters used to train a model, and selecting the best hyperparameter plays an important role in getting the best output performance. So, to overcome such problems we use Grid Search. Scikit-learn’s GridSearchCV (where CV stands for Cross Validation) trains the model for different hyperparameters entered by the…

In statistics, a moving average is a calculation used to analyze data points by creating a series of averages of different subsets of the full data set. In finance, a moving average (MA) is a stock indicator that is commonly used in technical analysis. …

Error Diffusion Dithering by Stucki is an approach for image dithering using error diffusion. In error diffusion, the quantization error of the current pixel is added to the pixel on the right and below according to the procedure below: a: For each point in the image, find the closest color…

There are various optimization algorithms that are used to find a local minimum of a differentiable function by minimizing the cost function of the problem. Gradient descent is one such algorithm that acts as an optimization algorithm that minimizes the cost function by updating the weights of the model. The…