Combining NLP Models and Creation of Custom rules using SpaCy Objective: In this article, we are going to create some custom rules for our requirements and will add that to our pipeline like explanding named entities and identifying person’s organization Read more
Feature Selection and CNN In this project we are going to build a neural network to predict if a particular bank customer is satisfies or not. To do this we are going to use Convolutional Neural Networks. The dataset which we Read more
Prediction of number of passengers for an airline using LSTM In this project we are going to build a model to predict the number of passengers in an airline. To do so we are going to use Recurrent Neural Networks, more Read more
NLP Tutorial – GloVe Vectors Embedding with TF2.0 and Keras GloVe stands for global vectors for word representation. It is an unsupervised learning algorithm developed by Stanford for generating word embeddings by aggregating a global word-word co-occurrence matrix from a corpus. The Read more
Star Rating Prediction of Amazon Products Reviews Objective In this notebook, we are going to predict the Ratings of Amazon products reviews by the help of given reviewText column. Natural Language Processing (NLP) is a sub-field of artificial intelligence that Read more
Prediction of Human Activity In this project we are going to use accelometer data to train the model so that it can predict the human activity. We are going to use 2D Convolutional Neural Networks to build the model. source = “Deep Neural Network Read more
Household Power Consumption Prediction using RNN-LSTM Power outage accidents will cause huge economic loss to the social economy. Therefore, it is very important to predict power consumption. Given the rise of smart electricity meters and the wide adoption of electricity Read more
Getting Started with spaCy This tutorial is a crisp and effective introduction to spaCy and the various NLP linguistic features it offers.We will perform several NLP related tasks, such as Tokenization, part-of-speech tagging, named entity recognition, dependency parsing and Visualization Read more
Deep learning with Tensorflow # pip install tensorflow==2.0.0-rc0 # pip install tensorflow-gpu==2.0.0-rc0 Watch Full Lesson Here: Objective Our objective for this code is to build to an Artificial neural network for classification problem using tensorflow and keras libraries. We will Read more
Classification using Fashion MNIST dataset What is TensorFlow? TensorFlow is one of the best libraries to implement deep learning. TensorFlow is a software library for numerical computation of mathematical expressional, using data flow graphs. Nodes in the graph represent mathematical operations, while the Read more
Visualizing statistical relationships Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Statistical analysis is a process of understanding how variables in a dataset relate to each Read more
Sentiment Classification Using DistilBERT Problem Statement We will use the IMDB Movie Reviews Dataset, where based on the given review we have to classify the sentiments of that particular review like positive or negative. The motivational BERT BERT became an essential Read more
Sentiment Analysis Objective In this notebook we are going to perform a binary classification i.e. we will classify the sentiment as positive or negative according to the `Reviews’ column data of the IMDB dataset. We will use TFIDF for text Read more
Multi-Label Text Classification In this notebook, we will use the dataset “StackSample:10% of Stack Overflow Q&A” and we use the questions and the tags data. We will be developing a text classification model that analyzes a textual comment and predicts Read more
Spam Ham text classification Watch Full Video Here Objective Our objective of this code is to classify texts into two classes spam and ham. What is Natural Language Processing Natural Language Processing (NLP) is the field of Artificial Intelligence, where Read more
Prediction of Google Stock Price using RNN In this we are going to predict the opening price of the stock given the highest, lowest and closing price for that particular day by using RNN-LSTM. Ref- https://colah.github.io/posts/2015-08-Understanding-LSTMs/ What is RNN? Recurrent Neural Read more
An Introduction to BERT Problem Statement We will use the IMDB Movie Reviews Dataset, where based on the given review we have to classify the sentiments of that particular review like positive or negative. Introduction Chatbots, virtual assistants, and dialog Read more
Sentiment Classification in Python In this notebook we are going to implement a LSTM model to perform classification of reviews. We are going to perform binary classification i.e. we will classify the reviews as positive or negative according to the Read more
Feature Selection Based on Univariate ROC_AUC for Classification and MSE for Regression Watch Full Playlist: https://www.youtube.com/playlist?list=PLc2rvfiptPSQYzmDIFuq2PqN2n28ZjxDH What is ROC_AUC The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance. Owing to its superiority in dealing with imbalanced and Read more
Feature Selection using Fisher Score and Chi2 (χ2) Test Watch Full Playlist: https://www.youtube.com/playlist?list=PLc2rvfiptPSQYzmDIFuq2PqN2n28ZjxDH What is Fisher Score and Chi2 ( χ2) Test Fisher score is one of the most widely used supervised feature selection methods. However, it selects each feature Read more