Modules is one of the best feature of Python. Except some core modules, you can install what you need and keep your Python setup smooth.
The integration of R with the TensorFlow package along with Keras has allowed developers to utilize TensorFlow’s functionalities with R. Deep learning has become easier for R users due to the integration of R Keras with Python’s tensorflow module. However,…
PyTorch is a popular Python library that helps all deep learning enthusiasts. The torch.nn module is a very important component of PyTorch which helps with the building and training of neural networks. In this article, we will take a deep…
Pytorch is a prevalent machine learning library in Python programming language. Pytorch is a handy tool in neural networks and torch.optim module is used in various neural network models for training. This module provides us with multiple optimization algorithms for…
Machine Learning is a diverse field growing continuously with applications spread across many domains like agriculture, finance, marketing, and many more. To utilize machine learning in any domain, we need first to build a model suitable for the use case.…
Imagine you are working on your dream machine-learning project in Python and collecting huge data from various sources. How do we integrate this huge data? Use data frames! A data frame is a table-like data storage format that stores data…
Tensors are primary data structures that are used widely for various purposes. Pytorch is a popular library in Python that contains these structures for various uses among researchers and data scientists. Similarly, the numerical Python or NumPy library is also…
Visualization is one of the most important parts of computation. From a very young age, we are advised to visualize coordinates on the x-y plane and to learn theoretical concepts using tools like flowcharts and diagrams. Visualization using various colors…
When it comes to machine learning or deep learning projects, the important and most crucial step after collecting and preprocessing data is the model selection. Choosing the right model will result in good accuracy on the training data and performance…
Imagine you are working on a big project that needs data from multiple sources. Agreed that collecting this data is cumbersome as it is, but storing the data together for easy access is an even more gruesome task. You would…
The Pandas library is regarded as the best Python tool for data analysis and storage. The library has several useful methods that export data from the Python environment to other compatible software and vice versa, cleaning and exploring the data.…