Author: Naveen
Some examples of simple gradient-based NLP models.
There are a lot of simple gradient-based NLP models that can be used to solve a variety of natural language processing tasks. Some of these include: Part-of-speech tagging: sentence parsing is a task that assigns part of speech tags to words in text and is used to analyze sentences. A task that assigns part of…
Read MoreHow is NLP revolutionizing financial services?
NLP is revolutionizing the way we interact with financial services. It’s allowing us to have a more natural conversation with our banks, and this is allowing us to do things that we couldn’t do before. How did you get into NLP? I got into NLP because I had a need, but it turns out that…
Read More5 things you must know about Computer Vision!
Computer Vision is a technology that enables machines to see, and it is one of the most important technologies in Artificial Intelligence. It is also one of the most difficult technologies to understand. for example, persons. How does machine vision work? The image data can be processed and an object in the image can be…
Read MoreWhat is upsampling and downsampling?
In a classification task, there is a high chance for the algorithm to be biased if the dataset is imbalanced. An imbalanced dataset is one in which the number of samples in one class is very higher or lesser than the number of samples in the other class. An example of an imbalanced dataset is…
Read MoreWhat is GMM and Agglomerative clustering?
A Gaussian mixture is a statistical model that assumes all the data points are generated from a linear combination of multivariate Gaussian distributions. This assumption has unknown parameters that can be estimated from the data, which we refer to as hyperparameters. Firstly, K-means employs the Gaussian distributions and centers of latent Gaussians. However, unlike K-means,…
Read MoreDifference between K-means and DBSCAN clustering?
Clustering involves grouping data points by similarity. In unsupervised machine learning, for example, data points are grouped into clusters depending on the information available in the dataset. The data items in the same clusters are similar to each other, while the items in different clusters are dissimilar. K Means and DBSCAN represent 2 of the…
Read MoreWhat is the difference between LSTM and GRU?
Introduction to LSTM (Long Short-Term Memory)Imagine you’re at a murder mystery dinner. At the very beginning, the Lord of the Manor suddenly collapses, and your task is to figure out, who done it? It could be the maid or the butler. However, there’s a problem: your short-term memory is not working. You can’t recall any…
Read MoreWhat is the difference between ANN and RNN?
ANN is a form of machine learning. It models the human brain and is a type of artificial neural network. ANNs are used to solve problems in the fields of computer vision, speech recognition, natural language processing, and other domains. .Artificial Intelligence is an umbrella term for a broad range of technologies that mimic the…
Read MoreWhat are Recommender Systems?
Recommender Systems are a type of AI that is used to predict what a user might like based on their interests, preferences, and historical data. The recommendation engine is personalized for the user, making suggestions that are not just based on similar tastes but also connections and social context. Recommendations include posts, products, or anything…
Read MoreDifference between R square and Adjusted R square?
Linear Regression, a machine learning algorithm, is widely used and evaluating its performance is essential. Two important metrics that are used to evaluate Linear Regression are R-squared and Adjusted R-squared. These metrics help determine the degree of the model fit and how much of the variance in the target variable is explained by the independent…
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