Tag: data science
NumPy for Data Science – Part 5
The difference between copy and view Copy View Join & split function Join array – joining means putting contents of two or more array in a single array. hstack vs vstack The major difference is that np.hstack combines NumPy arrays horizontally and np.vstack combines arrays vertically. Split – splitting breaks one array into multiple. NumPy…
Read MoreNumPy for Data Science – Part 4
Broadcasting NumPy Arrays The term broadcasting describes how NumPy treats arrays with different shapes during arithmetic operations. Subject to certain constraints, the smaller array is “broadcast” across the larger array in order that they have compatible shapes. NumPy operations are usually done on pairs of arrays on an element-by-element basis. Within the simplest case, the…
Read MoreNumPy for Data Science – Part 3
Arithmetic Operations in NumPy Arrays In NumPy there are multiple functions which we can use to perform the arithmetic operation, we will be looking them one by one. The add() function can also be used to perform the same operation. The subtract() function can also be used to perform the same operation. The multiply() function…
Read MoreNumPy for Data Science – Part 2
Create NumPy Arrays with Random Numbers Data Types in NumPy Arrays Shape and Reshaping In NumPy Arrays Shape of an Array The shape of an array is the number of elements in each dimension. Get the Shape of an Array NumPy arrays have an attribute called shape that returns a tuple with each index having the number…
Read MoreNumPy for Data Science – Part 1
What is NumPy Array? An array is a grid of values and it contains information about the raw data, how to locate an element, and how to interpret an element. Numpy vs Python List Advantages of using NumPy Arrays over Python List: Let’s look at the example of NumPy Array and Python List. Importance of…
Read MoreDifference between Data Science and Machine Learning
Data Science Data science is a field that studies data and how to extract meaning from it, using a series of methods, algorithms, systems, and tools to extract insights from structured and unstructured and unstructured data. That knowledge then gets applied to business, government, and other bodies to help drive profits, innovate products and services…
Read MoreDifference between Big Data and Data Science
Big Data Hugh volumes of data which cannot be handled using traditional database programming. Characterized by volume, variety, and velocity. Data Science A data-focused on scientific activity. Approaches to process big data. Harnesses the potential of big data for business decisions. Similar to data mining. Concept Big Data Diverse data types generated from multiple data…
Read MoreEnsemble Methods for Machine Learning: A Comprehensive Guide
Machine learning is a field that uses algorithms to analyze data and learn from it to make predictions and decisions. Ensemble methods are a set of techniques that have recently gained popularity due to their ability to combine several models and thus improve their predictive power. In this blog, we explore the concepts of ensemble…
Read MoreWhat is Machine Learning: Key Concepts & Real-World Applications
Machine Learning: The Key to Understanding How Computers Learn Machine learning is a branch of computer science that studies how computers can learn without any special programming. It is described as an important part of artificial intelligence (AI) because it enables computers to learn and improve their performance without special programming In recent years, machine…
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