There are many scenarios in which you have to detect any type of isolated polygons and overlapping polygons. But you also need to make it faster and 100 percent accurate when you pass the large numbers of polygons for processing. In this article, you’ll see exactly how to detect isolated and overlapping geo polygons in Python. Why do you need… Continue readingEasy way to detect isolated and overlapping geo polygons in Python
When working with geospatial data in Python, you might find yourself needing to create a perfectly round circle. The Shapely library is a popular tool for this task, but it’s not always as straightforward as it seems. Here is given code to create circle using Shapely library in python. The Shapely’s Buffer Function Dilemma You might think that Shapely’s buffer… Continue readingHow to Make a Circle Using the Shapely Library in Python
Let’s see how you can calculate the standard deviation or variance of the tensor. As you know while building a neural network, you have to perform aggregation on the tensor often. Finding maximum, minimum, and sum is done via the same piece of code with very little change in it. But finding variance or standard deviation will require some tweaks.… Continue readingEasy way to calculate the standard deviation or variance of the tensor in TensorFlow?
OpenAI’s ChatGPT-3(Generative Pre-trained Transformer) is one of the most powerful AI chatbots right now. You can ask anything and it gives the precise answers of it. OpenAI also provides API to implement it in the programming. In this article, we will see how to create a Chat GPT-3 web app with Streamlit in python using API. After creating this, your… Continue readingHow to Create A Chat GPT-3 Web app with Streamlit in Python
To reduce features in a dataset, two methods are there in machine learning: Feature selection and Feature extraction. Recursive feature elimination or in short RFE is the feature selection method. Here is given a complete guide on Recursive Feature Elimination for feature selection in machine learning. What is RFE? In Feature extraction, two or more features are combined from existing… Continue readingRecursive Feature Elimination(RFE): Effective Feature selection method in machine learning
There are many libraries in python available for making charts from the data. By which you can create charts and derive underlying information from the data. Plotly and Matplotlib are two of the libraries for it. Let’s see the comparison between Plotly vs Matplotlib and see which is best for performing the best data visualization in python. What is Matplotlib… Continue readingPlotly vs Matplotlib: Which is best for data visualization in python?
If you are doing Data science projects, then at the end you must have to make some web app or GUI so that you can demo your model or make that demo available to a large audience to use. With Gradio, you can create your machine learning web app very easily. Gradio is so easy that you can learn that… Continue readingGradio: Easy Guide for making ML web app for beginners
Classification machine learning algorithms use probability to predict the correct class, such as Logistic regression, SVC, decision tree classifier, Lasso regression, etc. Naive Bayes is the supervised machine learning algorithm used for classification problems. Let’s see how it works. Principle of Naive Bayes classifier The Naive Bayes classifier is one of the fastest and simplest algorithms in machine learning. The… Continue readingNaive Bayes Classifier in machine learning- All you need to know
When the model performs excellently on the training dataset but performs very very poorly on the testing or validation dataset that it is called that overfitting. So here you will see the 4 best ways to reduce overfitting in neural networks.
A machine learning pipeline consists of multiple data extraction, preprocessing, and model-building steps. It helps to automate processes that are required in model building. Pipeline helps to include all steps of preprocessing, feature selection, feature extraction, model selection, and model building In one entity. Here we will see how to make a pipeline in machine learning.