In the previous article, we learned about RNN’s and learnt that they have two problems that is vanishing gradients and exploding gradients. To overcome these problems, we have a state of the art method called LSTM- Long Short Term Memory. What are LSTM’s? Long Short-Term Memory (LSTM) networks are special RNNs, with different…

What are RNN’s and how do they work? Recurrent neural networks are a type of neural network used for sequential data. But before we dive deep into RNN’s lets understand what are neural networks. A Neural Network consists of different layers connected to each other, working on the structure and function of a human brain. …

What is AWS Comprehend? Comprehend is a AWS NLP service that allows users to gain insights from text data and build ML models. Go to AWS Comprehend- https://aws.amazon.com/comprehend/ Steps to perform classification using Comprehend: 1. Creating the classifier 2. Putting data into correct format. 3. Training 4. Make predictions (inference) Click on Custom Classification

The goal of building machine learning models is to reduce the error to the minimum so that we can have the best generic model that can preform well for any data set. Learn better and better models, such that overall model error gets smaller and smaller … ideally, as small…

Introduction Compact Prediction Trees are a type of algorithm used to solve sequence problems.Recently, they have gained a lot of attention due to their fast raining and performance efficiencies. LSTM’s/RNN’s suffer from one major drawback that is long training time, plus re-training of unseen items. Enter … CPT!!! Compact Prediction Tree To understand CPT,we…

What are Markov chains? A Markov chain is a mathematical stochastic process defined as a collection of random variables, that transition from one state to another according to certain probabilistic rules. What is the Markov Property? These set of transition satisfies the Markov Property, which states that the probability of transitioning to any particular state is dependent solely on…

What is Word Embedding? Word Embedding is a term used to describe numerical representation of text. We learnt some basic text vectoization techniques in the previous article such as Bag of Words, TF-IDF.. etc. Now let us look at some more advanced techniques for text representation. Creating a sparse representation using TF-IDF and other…

K Nearest Neighbor or K-NN is a supervised learning algorithm that uses a non-parametric algorithm, which means it does not make any assumption on underlying data. …

In the previous article, we talked about how we can achieve basic text processing for text data. For any machine learning model, input has to be in numerical format. Hence, once we pre-process the text, the next step in to vectorize the text, i.e …