Computer vision is the field of study which deals with automating tasks that rely on visual inputs. Computer vision aims to give computers the ability to understand images and video as humans do. Today, computer vision is a popular research area that has found applications in various fields such as Continue Reading
“Data analysis”
How to Use NumPy for Scientific Computing in Python
Introduction NumPy is a powerful library in Python that provides support for large, multi-dimensional arrays and matrices, along with a large collection of mathematical functions to operate on these arrays. It is one of the fundamental libraries for scientific computing in Python due to its efficient array operations and convenient Continue Reading
Working with Spark for big data analytics
Apache Spark is an open-source unified analytics engine for large-scale data processing. It is designed to be fast and general-purpose, making it ideal for big data processing tasks such as data preparation, machine learning, and graph processing. In this tutorial, we will cover the basics of working with Spark for Continue Reading
Introduction to data science
Data science is a constantly evolving field that applies scientific techniques, algorithmic and computational tools, and statistical methods to extract insights and knowledge from structured and unstructured data. In this tutorial, we will introduce you to the fundamentals of data science and its various components, including data acquisition, exploratory data Continue Reading
Big data processing with Spark
Introduction Apache Spark is an open-source distributed computing system designed for big data processing. It was initially developed at the University of California, Berkeley, and has become one of the most popular big data frameworks in the industry. With its powerful processing engine and intuitive API, Spark makes it easy Continue Reading
How to Use Pandas for Data Analysis in Python
Introduction Pandas is a powerful open-source data manipulation and analysis library for Python. It provides easy-to-use data structures and data analysis tools for handling and analyzing structured data. Pandas is built on top of NumPy, another popular library for scientific computing with Python. In this tutorial, we will learn how Continue Reading
How to Use NLTK for Text Analysis in Python
Text analysis is the process of extracting meaningful information from a given text. It involves tasks such as tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, and more. Natural Language Toolkit (NLTK) is a powerful library in Python that provides various tools and resources for text analysis. In this tutorial, Continue Reading
Big Data Analytics with Apache Spark
Apache Spark is an open-source, distributed computing system used for big data processing and analytics. It is designed to be faster, more efficient and easy to use than its predecessors like Hadoop MapReduce. Spark allows you to process large amounts of data in-memory, thereby providing high speed analytics and machine Continue Reading
How to Use SciPy for Scientific Computing in Python
Introduction Scientific computing is an essential aspect of many scientific and engineering disciplines. It involves the use of computers and algorithms to solve complex mathematical problems, perform data analysis, and simulate real-world systems. Python is a popular language for scientific computing due to its simplicity, versatility, and an extensive ecosystem Continue Reading
How to use LLMs for text segmentation and tagging
How to Use Language Model-Based Methods (LLMs) for Text Segmentation and Tagging In this tutorial, we will explore how to use Language Model-Based Methods (LLMs) for text segmentation and tagging. LLMs are powerful models that can generate coherent and structured text representations, allowing for a range of natural language processing Continue Reading