Python

Select columns in PySpark dataframe

Select columns in PySpark dataframe – A Comprehensive Guide to Selecting Columns in different ways in PySpark dataframe

Apache PySpark is a powerful big data processing framework, which allows you to process large volumes of data using the Python programming language. PySpark’s DataFrame API is a powerful tool for data manipulation and analysis. One of the most common tasks when working with DataFrames is selecting specific columns. In this blog post, we will …

Select columns in PySpark dataframe – A Comprehensive Guide to Selecting Columns in different ways in PySpark dataframe Read More »

Introduction to PySpark

Introduction to PySpark – Unleashing the Power of Big Data using PySpark

Introduction As we continue to generate massive volumes of data every day, the importance of scalable data processing and analysis tools cannot be overstated. One such powerful tool is Apache Spark, an open-source, distributed computing system that has become synonymous with big data processing. In this blog post, we will introduce you to PySpark, the …

Introduction to PySpark – Unleashing the Power of Big Data using PySpark Read More »

Install opencv python

Install opencv python – A Comprehensive Guide to Installing “OpenCV-Python”

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV-Python is a Python wrapper for the original OpenCV C++ library. Let’s see how it install OpenCV in python. Introduction OpenCV enables users to perform image and video processing tasks with ease. In this blog post, we will provide …

Install opencv python – A Comprehensive Guide to Installing “OpenCV-Python” Read More »

Install pip mac

install pip mac – How to install pip in MacOS?: A Comprehensive Guide

Pip is a widely used package manager for Python, allowing you to install and manage Python packages easily. In this blog post, we’ll explore various methods to install Pip on MacOS. I’ll provide clear, reproducible code examples for each method, making it easy for you to get started with Pip on your MacOS system. Using …

install pip mac – How to install pip in MacOS?: A Comprehensive Guide Read More »

Scrapy vs. Beautiful Soup: Which is better for web scraping?

Web scraping is the technique of extracting data from a specific website or web page. This has wide applications in: Research and publication purposes Competitor and market studies Creating data for machine learning models The extracted data can be stored in any format be it a csv, txt, json, API etc so that it can …

Scrapy vs. Beautiful Soup: Which is better for web scraping? Read More »

add Python to PATH – How to add Python to the PATH environment variable in Windows?

1. What is the purpose of adding Python to the PATH environment variable? Adding Python to the PATH environment variable in Windows allows you to run Python commands from any directory within the command prompt. Here are the steps to add Python to the PATH variable: 2. What is the PATH environment variable in Windows? …

add Python to PATH – How to add Python to the PATH environment variable in Windows? Read More »

An Introduction to AdaBoost

AdaBoost – An Introduction to AdaBoost

Adaboost is one of the earliest implementations of the boosting algorithm. It forms the base of other boosting algorithms, like gradient boosting and XGBoost. This tutorial will take you through the math behind implementing this algorithm and also a practical example of using the scikit-learn Adaboost API. Contents: What is boosting? What is Adaboost? Algorithm …

AdaBoost – An Introduction to AdaBoost Read More »

Numpy.random.randint() in python

Numpy.random.randint() in python

numpy.random.randint function is used to get random integers from low to high values. The low value is included while the high value is excluded in the calculations. The output values are taken from the discrete uniform distribution of the range values. random.randint(low, high=None, size=None, dtype=int) Purpose: The numpy random randint function used for creating a …

Numpy.random.randint() in python Read More »

np.random.uniform

How to use numpy.random.uniform() in python.

The np.random.uniform() function is used to create an array with random samples from a uniform probability distribution of given low and high values. random.uniform(low=0.0, high=1.0, size=None) Purpose: The numpy random uniform function used for creating a numpy array with random float values from low to high interval. Parameteres: Low: float or array-like of floats,optional: Lowest …

How to use numpy.random.uniform() in python. Read More »

Train Test Split – How to split data into train and test for validating machine learning models?

The train-test split technique is a way of evaluating the performance of machine learning models. Whenever you build machine learning models, you will be training the model on a specific dataset (X and y). Once trained, you want to ensure the trained model is capable of performing well on the unseen test data as well. …

Train Test Split – How to split data into train and test for validating machine learning models? Read More »

Python

Decorators in Python – How to enhance functions without changing the code?

Decorators in python allow you to dynamically change the functionality of another function, without altering it’s code. What? Is that possible? Yes. This covers: 1. What is a decorator and how to create one? 2. Easier way to decorate functions 3. Class decorators 4. Problem with docstrings on decorated functions and how to solve. What …

Decorators in Python – How to enhance functions without changing the code? Read More »

Python

Generators in Python – How to lazily return values only when needed and save memory?

Generators in python provide an efficient way of generating numbers or objects as and when needed, without having to store all the values in memory beforehand. Introduction You can think of Generators as a simple way of creating iterators without having to create a class with __iter__() and __next__() methods. So how to create a …

Generators in Python – How to lazily return values only when needed and save memory? Read More »

Python

Object Oriented Programming (OOPS) in Python

Object oriented programming is an effective way of writing code. You create classes which are python objects, that represented meaningful entities which defines its own behaviour (via methods) and attributes. Let’s understand what a class is and the concepts behind Object Oriented Programming in Python Everything you have encountered so far in Python, such as …

Object Oriented Programming (OOPS) in Python Read More »

Course Preview

Machine Learning A-Z™: Hands-On Python & R In Data Science

Free Sample Videos:

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science