Automatic Text Generation Automatic text generation is the generation of natural language texts by computer. It has applications in automatic documentation systems, automatic letter writing, automatic report generation, etc. In this project, we are going to generate words given a set of input words. We are going to train the Read more…
Extraction of text from PDF using PyPDF2 This notebook demonstrates the extraction of text from PDF files using python packages. Extracting text from PDFs is an easy but useful task as it is needed to do further analysis of the text. Working with .PDF Files We are going to use PyPDF2 for Read more…
Free Full HD Desktop Wallpaper Download from Unsplash API – How to Use Unsplash API Unsplash is a website that offers users free photos to download on your desktop. Moreover, it’s a license-free user can use it for personal use. You can search the photo as your criteria and got Read more…
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 name from a given text. For example: For example, the 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 are going to use contains 370 features. We are going 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 precisely Long Short Term Memory. Recurrent Neural Network Neural Networks are 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 resulting embeddings show interesting linear substructures of the word in 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 deals understanding and processing human language. In light of new 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 Example” by Nils Ackermann is licensed under Creative Commons CC 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 generation technology like solar panels, there is a wealth of 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 using displaCy. spaCy is a free, open-source library for advanced Natural 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 try to learn how to build a nerual netwroks model 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 edges represent the multidimensional data arrays (tensors) that flow between 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 other and how those relationships depend on other variables. Visualization 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 ingredient of many NLP deep learning pipelines. It is considered 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 data vectorization and Linear Support Vector Machine for classification. Natural 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 multiple labels associated with the questions. We will implement a 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 we analyse text using machine learning models Application of NLP 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 Networks are the first of its kind State of the 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 agents will typically classify queries into specific intents in order Read more…