## How to Become a Successful Machine Learning Engineer

Machine learning is a rapidly growing field that offers a wide range of opportunities for those who have the right skills and qualifications. As a machine learning engineer, you will be responsible for designing and implementing machine learning models that can help organizations make data-driven decisions. If you’re interested in Read more…

## Feature Engineering Tutorial Series 6: Variable magnitude

Does the magnitude of the variable matter? In Linear Regression models, the scale of variables used to estimate the output matters. Linear models are of the type y = w x + b, where the regression coefficient w represents the expected change in y for a one unit change in x Read more…

## Feature Engineering Tutorial Series 5: Outliers

An outlier is a data point which is significantly different from the remaining data. “An outlier is an observation which deviates so much from the other observations as to arouse suspicions that it was generated by a different mechanism.” [D. Hawkins. Identification of Outliers, Chapman and Hall , 1980.] Should Read more…

## Feature Engineering Tutorial Series 4: Linear Model Assumptions

Linear models make the following assumptions over the independent variables X, used to predict Y: There is a linear relationship between X and the outcome Y The independent variables X are normally distributed There is no or little co-linearity among the independent variables Homoscedasticity (homogeneity of variance) Examples of linear Read more…

## Feature Engineering Series Tutorial 2: Cardinality in Machine Learning

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…

## Matplotlib Crash Course

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 with Pandas

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…

## Pandas Crash Course

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…

## Processing Pipeline in SpaCy

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…

## Working with Text Files in Python for NLP

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…

## LinkedIn Profile Scrapper in Python

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…

## Text Summarization using NLP

Extractive Text Summarization What is text summarization? Text summarization is the process of creating a short, accurate, and fluent summary of a longer text document. It is the process of distilling the most important information from a source text. Automatic text summarization is a common problem in machine learning and Read more…

## Extract Text from PDF Files in Python for NLP

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…

###### Machine Learning

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…

## SpaCy – Introduction for NLP | Combining NLP Models and Custom rules

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…

## Star Rating Prediction

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…

## Human Activity Recognition Using Accelerometer Data

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…

## Multi-step-Time-series-predicting using RNN LSTM

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…

## Complete Seaborn Python Tutorial for Data Visualization in Python

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…

## DistilBERT – Smaller, faster, cheaper, lighter and ofcourse Distilled!

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…