Understand the basics of software development tools — High-level languages are designed to be more human-readable and programmer-friendly. They provide a higher level of abstraction from the underlying hardware and are closer to natural language compared to low-level languages. High-level languages are typically platform-independent and offer built-in functions and libraries that simplify programming tasks.

A useful concept for a modular python application — In Python, the function can be passed as an argument, a function can return another function, and can be used function inside another function. Here are a few examples to help you understand decorators better: Example 1: Simple function decorator def uppercase_decorator(func): def wrapper()…

Initialization and cleanup methods in classes — Constructor In, Python, when we create an instance or object of a class, it calls a constructor function in the class. It is used to initialize the object’s attributes and perform any necessary setup tasks. In Python, the constructor method is named __init__(). It is defined within a class and…

Analyzing the patterns, trends, and seasonality in time series data — Time series analysis is a branch of machine learning and statistics that deal with data points collected sequentially over time. It involves analyzing the patterns, trends, and dependencies present in the time series data to make predictions or extract insights. Machine learning models can be used effectively for time series…

Useful theory for data science and machine learning — Word embeddings are a fundamental concept in natural language processing (NLP) that represent words as continuous vector representations in a multi-dimensional space. These vector representations capture the semantic and syntactic meaning of words, allowing NLP models to learn meaningful relationships between words and perform various tasks such as text classification…

Handful explanation of natural language processing techniques — NLP stands for Natural Language Processing. It is a branch of artificial intelligence (AI) that focuses on enabling computers to understand, interpret, and generate human language in a way that is both meaningful and useful. Natural Language Processing involves the interaction between computers and humans through natural language, which includes…

Guide to the topics for deep neural networks — Fundamentals of Machine Learning: Before diving into deep learning, it’s important to have a solid understanding of machine learning fundamentals, including concepts such as supervised learning, unsupervised learning, feature engineering, model evaluation, and optimization. Neural Networks: Deep learning is based on neural networks, so understanding the architecture, components, and activation…

The advanced topic for Python applications — Object-oriented programming (OOP) is a programming paradigm that allows you to organize your code into objects, which are instances of classes. Python is an object-oriented programming language that provides support for classes, objects, encapsulation, inheritance, and polymorphism, which are the fundamental principles of OOP. …

Useful uses in the python applications — Pseudorandom number generators for different distributions, such as integer and float, are implemented in Python through the random module. To implement a random module in Python, have to simply apply it using the “import” command in Python. Example: import random print(random.random()) #output: 0.17302581315380994 It is the most basic function using…