As real estate moves towards digitization and automation, Automated Valuation Model (AVM) replaces traditional valuation methods. . What is AVM? How is it used in real estate valuation?Read More
The main aim of this project is to make a model that correctly classifies the weather states on the images it sees.
This seems pretty easy but the main challenge the model will face is that it doesn’t need to learn about the shapes of the objects in the image.
k-Nearest Neighbors (KNN) is a supervised machine learning algorithm that can be used for either regression or classification tasks. KNN is non-parametric, which means that the algorithm does not make assumptions about the underlying distributions of the data.Read More
Matplotlib provides a handy function called contour(), which can insert the colors between points. However, as the documentation suggested, we need to define the grid of points Xof yin the feature space. The beginning point would be to find the maximum value and minimum value of each feature then increase by one to make sure that the whole space is covered.Read More
Clickbait is false advertising links whose purpose is to get clicked at any cost. See how the problem has been tackled through Natural Language Processing and text classification to reduce the level of fake links.Read More
Meta Learners: An algorithm that is used to combine the base estimators is called the meta learner. We can determine how we want this algorithm to respond to different predictions from other models (classifiers in this case).Read More
Feedback analysis with Lightgbm classifier. Objective: to analyze travelers ‘feelings’ on Twitter posts. It would be fascinating for airlines to use this free data to provide better service to their customers.Read More
Use of hate speech and offensive language on social media is a growing challenge. This can effect the mental health of a person against whom the hate speech or offensive language is being expressed, with sometimes devastating effects. In order solve or help solving this problem, text classification can be used, so a message on social media can be tagged as hate speech or offensive language.Read More
In this article, I would like to take our dataset a step further to solve a sentiment classification problem. Specifically, we will be assigning sentiment targets to each review and then using a binary classification algorithm to predict those targets.Read More
As the arsenal of classification algorithms increased dramatically, it became more and more tempting to use several classifiers and then combine their decisions to gain accuracy and avoid the burden of choosing the right one.Read More
Explore practical ways to optimize your model’s hyperparameters with grid search, randomized search, and bayesian optimization.Read More
Image segmentation with K-Means clustering is an important step in image processing, and it seems everywhere if we want to analyze what is inside the image.Read More
Recent developed deep unsupervised methods allow us to jointly learn representation and cluster unlabeled data through Deep comprehensive Correlation Mining, focusing on the correlation among samples.Read More