Author Archives: Ankit Das - Page 3
Neural Network uses optimising strategies like stochastic gradient descent to minimize the error in the algorithm. The way we actually compute this error is by using a Loss Function. It is used to quantify how good or bad the model is performing. These are divided into two categories i.e.Regression loss and Classification Loss.
The post Loss Functions in Deep Learning: An Overview appeared first on Analytics India Magazine.
Neural Network uses optimising strategies like stochastic gradient descent to minimize the error in the algorithm. The way we actually compute this error is by using a Loss Function. It is used to quantify how good or bad the model is performing. These are divided into two categories i.e.Regression loss and Classification Loss.
The post Loss Functions in Deep Learning: An Overview appeared first on Analytics India Magazine.
Neural Network uses optimising strategies like stochastic gradient descent to minimize the error in the algorithm. The way we actually compute this error is by using a Loss Function. It is used to quantify how good or bad the model is performing. These are divided into two categories i.e.Regression loss and Classification Loss.
The post Loss Functions in Deep Learning: An Overview appeared first on Analytics India Magazine.
LSTM autoencoder is an encoder that makes use of LSTM encoder-decoder architecture to compress data using an encoder and decode it to retain original structure using a decoder.
The post Introduction to LSTM Autoencoder Using Keras appeared first on Analytics India Magazine.
In recent times, there has been a lot of emphasis on Unsupervised learning. Studies like customer segmentation, pattern recognition has been a widespread example of this which in simple terms we can refer to as Clustering. We used to solve our problem using a basic algorithm like K-means or Hierarchical Clustering. With the introduction of Gaussian mixture modelling clustering data points have become simpler as they can handle even oblong clusters. It works in the same principle as K-means but has some of the advantages over it.
The post Gaussian Mixture Model Clustering Vs K-Means: Which One To Choose appeared first on Analytics India Magazine.
Language modelling is the speciality of deciding the likelihood of a succession of words. These are useful in many different Natural Language Processing applications like Machine translator, Speech recognition, Optical character recognition and many more.In recent times language models depend on neural networks, they anticipate precisely a word in a sentence dependent on encompassing words. However, in this project, we will discuss the most classic of language models: the n-gram models.
The post Complete Guide on Language Modelling: Unigram Using Python appeared first on Analytics India Magazine.
Recommendation systems expect to foresee clients' inclinations and predict the most likely product that the users are most likely to purchase and are of interest to them. Organizations utilizing recommendation frameworks centre around expanding deals because of exceptionally customized offers and an upgraded client experience. Netflix, Amazon, and so forth use recommender frameworks to assist their clients with recognizing the right item or films for them.
The post Hands-On Guide To Recommendation System Using Collaborative Filtering appeared first on Analytics India Magazine.
Information Extraction is a process of extracting information in a more structured way i.e., the information which is machine-understandable. It consists of subfields which cannot be easily solved. Therefore, an approach to store data in a structured manner is Knowledge Graph which is a set of three-item sets called Triple where the set combines a subject, a predicate and an object.
The post Complete Guide to Implement Knowledge Graph Using Python appeared first on Analytics India Magazine.
Machine learning algorithms may take a lot of time working with large datasets. To overcome this a new dimensional reduction technique was introduced. If the input dimension is high Principal Component Algorithm can be used to speed up our machines.
The post Principal Component Analysis On Matrix Using Python appeared first on Analytics India Magazine.
Do you realize you can google up anything today and can be sure to find something related to it on the internet? This comes from the huge amount of text data available freely for us. You must be intrigued enough to use all this data for your machine learning models. The problem is, machines don’t…
The post Hands-On Guide To Different Tokenization Methods In NLP appeared first on Analytics India Magazine.