by Team AHT | Jul 29, 2024 | AI & ML
Data preprocessing is a crucial step in machine learning. It involves cleaning and transforming raw data into a format suitable for modeling. Data Cleaning Data cleaning involves identifying and correcting errors, inconsistencies, and inaccuracies in the data such as... by Team AHT | Jul 29, 2024 | AI & ML
In this lesson, we’ll cover essential Python libraries for machine learning: NumPy, Pandas, Matplotlib, and Scikit-Learn. NumPy NumPy is a library for numerical computations in Python. It provides support for arrays, matrices, and many mathematical functions.... by Team AHT | Jul 29, 2024 | AI & ML
What is AI? Artificial Intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and learn like humans. AI systems can perform tasks such as visual perception, speech recognition, decision-making, and language translation. What... by Team AHT | Jul 29, 2024 | AI & ML
My Posts in this series will follow below said topics. Introduction to AI and ML What is AI? What is Machine Learning? Types of Machine Learning Supervised Learning Unsupervised Learning Reinforcement Learning Key Terminologies Python for Machine Learning Introduction... by Team AHT | Jul 29, 2024 | AI & ML
What is AI? Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These systems can perform tasks that typically require human intelligence, such as visual perception, speech recognition,... by Team AHT | Jul 28, 2024 | Python
Python provides various libraries and functions to manipulate dates and times. Here are some common operations: DateTime Library The datetime library is the primary library for date and time manipulation in Python. datetime.date: Represents a date (year, month, day)... by Team AHT | Jul 26, 2024 | Pyspark
Optimization in PySpark is crucial for improving the performance and efficiency of data processing jobs, especially when dealing with large-scale datasets. Spark provides several techniques and best practices to optimize the execution of PySpark applications. Before... by Team AHT | Jul 25, 2024 | Pyspark, SAS
Let us create a comprehensive SAS project that involves merging, joining, transposing large tables, applying PROC SQL lead/rank functions, performing data validation with PROC FREQ, and incorporating error handling, macro variables, and macros for various functional... by Team AHT | Jul 23, 2024 | Python
Error and Exception Handling: Python uses exceptions to handle errors that occur during program execution. There are two main ways to handle exceptions: 1. try-except Block: The try block contains the code you expect to execute normally. The except block handles... by Team AHT | Jul 21, 2024 | Python
I believe you read our Post https://www.hintstoday.com/i-did-python-coding-or-i-wrote-a-python-script-and-got-it-exected-so-what-it-means/. Before starting here kindly go through the Link. How the Python interpreter reads and processes a Python script The Python... by Team AHT | Jul 16, 2024 | Pyspark
Adaptive Query Execution (AQE) in Apache Spark 3.0 is a powerful feature that brings more intelligent and dynamic optimizations to Spark SQL on runtime statistics. By adapting the execution plan at runtime based on actual data statistics, AQE can provide significant... by Team AHT | Jul 15, 2024 | AI & ML
Training for Generative AI is an exciting journey that combines knowledge in programming, machine learning, and deep learning. Since you have a basic understanding of Python, you are already on the right track. Here’s a suggested learning path to help you progress: 1.... by Team AHT | Jul 12, 2024 | Python
Linked lists are a fundamental linear data structure where elements (nodes) are not stored contiguously in memory. Each node contains data and a reference (pointer) to the next node in the list, forming a chain-like structure. This dynamic allocation offers advantages... by Team AHT | Jul 10, 2024 | Python
In Python, classes and objects are the fundamental building blocks of object-oriented programming (OOP). A class defines a blueprint for objects, and objects are instances of a class. Here’s a detailed explanation along with examples to illustrate the concepts...
by Team AHT | Jul 9, 2024 | Python
It is a case sensitive, non-mutable sequence of characters marked under quotation. It can contain alphabets, digits, white spaces and special characters. In Python, a string is a sequence of characters enclosed within either single quotes (‘ ‘), double... by Team AHT | Jul 9, 2024 | Tutorials
Regular expressions (regex) are a powerful tool for matching patterns in text. Python’s re module provides functions and tools for working with regular expressions. Here’s a complete tutorial on using regex in Python. 1. Importing the re Module To use... by Team AHT | Jul 7, 2024 | Pyspark
Let us create One or Multiple dynamic lists of variables and save it in dictionary or Array or other datastructure for further repeating use in Pyspark projects specially for ETL jobs. Variable names are in form of dynamic names for example Month_202401 to... by Team AHT | Jul 7, 2024 | Pyspark
Error handling, debugging, and generating custom log tables and status tables are crucial aspects of developing robust PySpark applications. Here’s how you can implement these features in PySpark: 1. Error Handling in PySpark PySpark provides mechanisms to handle... by Team AHT | Jul 7, 2024 | Pyspark
Here is a detailed approach for dividing a monthly PySpark script into multiple code steps. Each step will be saved in the code column of a control DataFrame and executed sequentially. The script will include error handling and pre-checks to ensure source tables are... by Team AHT | Jul 7, 2024 | Pyspark
String manipulation is a common task in data processing. PySpark provides a variety of built-in functions for manipulating string columns in DataFrames. Below, we explore some of the most useful string manipulation functions and demonstrate how to use them with... by Team AHT | Jul 6, 2024 | Pyspark
Here’s a comprehensive list of some common PySpark date functions along with detailed explanations and examples on Dataframes(We will again discuss thess basis Pyspark sql Queries): 1. current_date() Returns the current date. from pyspark.sql.functions import... by Team AHT | Jul 3, 2024 | Pyspark
Window functions in PySpark allow you to perform operations on a subset of your data using a “window” that defines a range of rows. These functions are similar to SQL window functions and are useful for tasks like ranking, cumulative sums, and moving... by Team AHT | Jul 2, 2024 | Pyspark
PySpark provides a powerful API for data manipulation, similar to pandas, but optimized for big data processing. Below is a comprehensive overview of DataFrame operations, functions, and syntax in PySpark with examples. Creating DataFrames Creating DataFrames from... by Team AHT | Jul 1, 2024 | Pyspark
In PySpark, you can perform operations on DataFrames using two main APIs: the DataFrame API and the Spark SQL API. Both are powerful and can be used interchangeably to some extent. Here’s a breakdown of key concepts and functionalities: 1. Creating DataFrames:...
