For this Machine Learning project, we will use the “Walmart Recruiting – Store Sales Forecasting” dataset, from Kaggle. The goal is to predict the Weekly Sales for specific stores, departments and dates. Download Data First, we install the opendatasets library. In [1]: pip install opendatasets –upgrade…

For this EDA project, I will use the “Hotel booking demand” dataset, which can be found here This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the…

Introduction NumPy is an open-source extension for Python that allows us to use vectors and matrices. We can also use it to work in the domain of linear algebra and fourier transforms. By using this library, we can get faster results than those obtained from…

In this post, we will use PyTorch to go through different models to classify images from the COIL-100 dataset and compare their performance. COIL-100 Dataset Columbia University Image Library (COIL-100) is a dataset of color images of 100 objects. The objects were placed on a…

In this post, we will learn how to build a deep learning model in PyTorch by using the CIFAR-10 dataset. PyTorch PyTorch is a Machine Learning Library created by Facebook. It works with tensors, which can be defined as a n-dimension matrix from which you…

Through linear regression, we can predict values based on the corelation of variables. This can be very helpful in areas such as retail and e-commerce, where stores want to know the best selling price for their products. There are many good tools that we can…

Lately, PyTorch has gain a lot of popularity among the data science community, as one of the most used Deep Learning libraries. This library is based on tensors, which can be understood as a n-dimension matrix from which you can perform mathematical operations and build…