Parking Lot Occupancy K-means Analysis in National Parks in the United States
Introduction The objective of this study is to determine the correlation that exists in the levels of occupancy of park parking lots in the United States regarding the months, days and hours of an analyzed period from the development of a k-means algorithm. To achieve…
Forecasting model for influenza A cases (H7N9) based on Random Forests
The objective of this study is to present a machine learning model based on Random Forests that allows predicting the number of deceased and recovered patients who have contracted the influenza A (H7N9) virus in China during 2013. To do this, I used a data…
Walmart — Store Sales Forecasting
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…
Hotel Booking Demand EDA
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…
5 NumPy Functions that you Should Know
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…
Image Classification with COIL-100 Dataset in PyTorch
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…
Deep Learning in PyTorch with CIFAR-10 dataset
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…
Cars price prediction through linear regression with PyTorch
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…
5 Useful tensor functions for PyTorch
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…