Cardinality refers to the number of possible values that a feature can assume. For example, the variable “US State” is one that has 50 possible values. The binary features, of course, could only assume one of two values (0 or 1). The values of a categorical variable are selected from Read more…
Missing data, or missing values, occur when no data / no value is stored for certain observations within a variable. Incomplete data is an unavoidable problem in most data sources, and may have a significant impact on the conclusions that can be derived from the data. Why is data missing? The source of missing Read more…
One of the central concepts of data science is gaining insights from data. Statistics is an excellent tool for unlocking such insights in data. In this post, we’ll see some basic types of data(variable) which can be present in your dataset. What is a Variable? A variable is any characteristic, Read more…
How to use Pre-trained VGG16 models to predict object The VGG network architecture was introduced by Simonyan and Zisserman in their 2014 paper, Very Deep Convolutional Networks for Large Scale Image Recognition. This network is characterized by its simplicity, using only 3×3 convolutional layers stacked on top of each other Read more…
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It is a cross-platform library for making 2D plots from data in arrays. It can be used in Python and IPython shells, Jupyter notebook and web application servers also. Matplotlib is written in Python and makes Read more…
Data visualization is the discipline of trying to understand data by placing it in a visual context so that patterns, trends and correlations that might not otherwise be detected can be exposed. pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, in Python programming Read more…
What is Pandas? pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, in Python programming language. It is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. Read more…
Resume NER Training In this blog, we are going to create a model using SpaCy which will extract the main points from a resume. We are going to train the model on almost 200 resumes. After the model is ready, we will extract the text from a new resume and Read more…
Word Embedding and Sentiment Analysis What is Word Embedding? Natural Language Processing(NLP) refers to computer systems designed to understand human language. Human language, like English or Hindi consists of words and sentences, and NLP attempts to extract information from these sentences. Machine learning and deep learning algorithms only take numeric Read more…
Sentiment Classification using SpaCy What is NLP? Natural Language Processing (NLP) is the field of Artificial Intelligence concerned with the processing and understanding of human language. Since its inception during the 1950s, machine understanding of language has played a pivotal role in translation, topic modeling, document indexing, information retrieval, and Read more…
What is SpaCy? spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. If you’re working with a lot of text, you’ll eventually want to know more about it. For example, what’s it about? What do the words mean in context? Who is doing what to whom? Read more…
Text Extraction in SpaCy spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. If you’re working with a lot of text, you’ll eventually want to know more about it. For example, what’s it about? What do the words mean in context? Who is doing what to Read more…
Text Extraction and Matching spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. If you’re working with a lot of text, you’ll eventually want to know more about it. For example, what’s it about? What do the words mean in context? Who is doing what to Read more…
Working with the text files Working with f-strings for formated print Working with .CSV, .TSV files to read and write Working with %%writefile to create simple .txt files [works in jupyter notebook only] Working with Python’s inbuilt file read and write Watch full video here: String Formatter String formatting enables Read more…
Multi-Label Image Classification in Python In this project, we are going to train our model on a set of labeled movie posters. The model will predict the genres of the movie based on the movie poster. We will consider a set of 25 genres. Each poster can have more than Read more…
LinkedIn Profile Scrapping using Selenium and Beautiful Soup Scraping of LinkedIn profiles is a very useful activity especially to achieve public relations/marketing tasks. In this project, we are going to scrap important data from a LinkedIn profile. The first part of this project is to automatically log in to our Read more…
What is CNN This Notebook demonstrates training a simple Convolutional Neural Network (CNN) to classify CIFAR images. Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. Unlike traditional multilayer perceptron architectures, it uses two operations Read more…
Auto Connect Bot for LinkedIn In this project, we are going to create a bot that finds the people in your LinkedIn suggestions and sends a connection request to each one of them with a message. It also finds the suggestions of your suggestions and sends them a connection request. Read more…
Breast Cancer Detection Using CNN in Python Breast cancer is the most commonly occurring cancer in women and the second most common cancer overall. There were over 2 million new cases in 2018, making it a significant health problem in present days. The key challenge in breast cancer detection is Read more…
Use of Dropout and Batch Normalization in 2D CNN on Dog Cat Image Classification in TensorFlow 2.0 We are going to predict cat or dog by the help of Convolutional neural network. I have taken the dataset from kaggle https://www.kaggle.com/tongpython/cat-and-dog. In this dataset there is two class cats and dogs Read more…