Channel Title: Venkata Reddy AI Classes Channel Description: 🚀 Corporate Trainer in Data Science, Machine Learning & AI 📚 Author & Educator: Books available worldwide "Machine Learning and Deep Learning using Python and TensorFlow" "Practical Business Analytics using SAS" 🌟 Professional Expertise: With a robust foundation in Data Science, I specialize in transforming complex concepts into actionable knowledge. My journey has been marked by deep involvement in credit risk model building, market response modeling, social media analytics, revenue forecasting, and advanced machine learning techniques. 👩‍🏫 Corporate Training Dynamo: Having delivered over 200 corporate training sessions and helped more than 5000 students, my experience spans across 25+ esteemed organizations. I am passionate about sharing knowledge and empowering professionals to harness the power of Data Science and AI in their respective fields. 💼 Specializations: Data Science Machine Learning Deep Learning 🔧 Tools of the Trade: R Python SAS <video> Python Data Structures | Video 2 | Part 3 (Tuple Data Type) | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LCkNoOkMHOgiG6c-vlBo9qHL8CkLkA00#scrollTo=_iOyW0aOdDr0 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00: Overview of Course Contents 00:17: Significance of Built-in Data Types 00:44: Introduction to Tuples Explained 01:15: Steps to Define Tuples 03:45: How to Work with Tuples 04:35: Key Advantages of Tuples 07:19: Understanding Tuple Packing 10:17: Difference between Lists & Tuples 16:30: Selecting the Right Data Type in Real-life Situations 20:41: Next Steps Tuples are a key data type in Python that many programmers find essential due to their immutability. Unlike lists, which are mutable and use square brackets, tuples are created with parentheses and cannot be changed once defined, making them memory-efficient and often faster, especially in handling large datasets. Lists allow you to modify elements directly, but attempting to do the same with a tuple results in an error, as tuples provide a stable data structure for situations where data should remain static. #PythonTutorial #PythonLists #DataStructures #ProgrammingBasics #PythonForBeginners #DataAnalysis #PythonDictionary #CodingFundamentals #PythonIndexing #PythonSlicing #PythonBasics #dataanalysis #ai #promptengineering #genai </video> <video> Python NumPy | Video 3 | Part 3 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LTWEn-pSCA8ecvQknaftn1gKbWp7XdM2?authuser=3 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Course Introduction and Overview 00:17 - Boolean Indexing Explained 09:39 - Array Subset Creation Techniques 20:35 - Understanding Array Placeholders 21:03 - Introduction to np.zeros() 21:57 - np.ones() Function and Its Uses 24:17 - Detailed Look at Python’s arange() Function 25:33 - Creating 2D Arrays with arange() 27:28 - Using np.linspace() for Range Generation 28:29 - Closing Remarks 29:10 - Next Steps and Future Plans Boolean indexing in Python is a powerful way to filter arrays or DataFrames based on conditions. Instead of using positional indices, Boolean indexing evaluates conditions like age greater than 35 and returns only the values that meet the criteria. To apply this, import the necessary libraries, define a condition, and filter the data with condition. This simplifies data selection without using complex loops. Boolean indexing is fast, efficient, and essential for handling large datasets, making it a must-have tool for data analysts and Python programmers. #Python #DataScience #BooleanIndexing #NumPy #Pandas #PythonProgramming #ArrayManipulation #DataFiltering #PythonTips #CodingSkills #LearnNumPy #DataAnalysis #ai #promptengineering #genai </video> <video> Python Data Structures | Video 2 | Part 4 (Dictionary Data Type) | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LCkNoOkMHOgiG6c-vlBo9qHL8CkLkA00#scrollTo=_iOyW0aOdDr0 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 Course Contents Overview 00:17 Intro to Dictionaries 02:43 Understanding Key-Value Pairs 03:05 How to Define Dictionaries 05:34 Accessing Dictionary with Keys 07:15 Updating Dictionary Values 10:52 Retrieving Keys or Values 11:37 Looping through Dictionary 17:40 Hands-on Exercise on Dictionary 22:30 Single vs. Double Quotes 26:07 What’s Next Explore the essentials of Python dictionaries in this comprehensive guide. Learn how to define and access dictionaries, understand key-value pairs, and modify values effectively. Discover looping techniques, retrieve keys or values with ease, and dive into practical exercises that strengthen your understanding. We’ll also clarify the use of single vs. double quotes in Python, setting you up for success in your coding journey. Perfect for beginners and intermediates eager to master dictionary operations and enhance their programming skills. #PythonTutorial #PythonLists #DataStructures #ProgrammingBasics #PythonForBeginners #DataAnalysis #PythonDictionary #CodingFundamentals #PythonIndexing #PythonSlicing #PythonBasics #dataanalysis #ai #promptengineering #genai </video> <video> Python Data Structures | Video 2 | Part 5 (Set Data Type) | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LCkNoOkMHOgiG6c-vlBo9qHL8CkLkA00#scrollTo=_iOyW0aOdDr0 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 Course Contents Overview 00:17 Intro to Sets Data Type 02:18 Defining sets 03:35 Different way to define sets 07:03 Set Operations 08:47 Significance of Data Types 09:58 What’s Next Explore Python's Set Data Type in this video and discover how it works as a collection of unordered, unique values. Understand its differences from lists and dictionaries and learn how to manage unique data efficiently. We’ll cover essential operations like union, intersection, and symmetric difference, and discuss avoiding common mistakes, such as misusing curly braces. With practical examples involving products and orders, you'll see set operations in action. #PythonProgramming #PythonDataTypes #LearnPython #SetOperations #CodingBasics #PythonTutorial #DataScience #ProgrammingConcepts #CodingFundamentals #PythonIndexing #PythonSlicing #PythonBasics #dataanalysis #ai #promptengineering #genai </video> <video> Python Pandas | Video 5 | Part 3 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1Ll4R7lZSp3_5Yi3wyFscGLndspAYrYYW Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Introduction to the Course 00:18 - Advanced Pandas Commands Explained 02:48 - New Column Creation via For Loop 04:50 - Checking Unique Value Counts 06:01 - Basics of Vectorization 08:32 - Efficiency Test: For Loop Vs. Vectorization 17:40 - Lab Session: Comparing Methods 19:10 - Applying Functions in Pandas 19:10 - Overview of User-Defined Functions 22:02 - How to Create Columns with Apply 28:28 - Apply Function for Columns 33:56 - Additional User-Defined Function Examples 37:46 - Hands-On: Apply Function Lab 38:12 - Wrapping Up: What’s Next This session explores Python efficiency by comparing the performance of for loops and vectorization in Pandas for data manipulation and apply function. Learn how vectorization significantly reduces processing time by handling entire datasets at once, unlike the slower, row-by-row for loops. Through practical examples, such as segmenting credit card usage and categorizing unit prices, we showcase real-world applications. You'll also discover how Boolean indexing and multiple conditions can optimize workflows while avoiding common pitfalls in handling large datasets. Master Pythonic techniques to write faster, scalable code for data analysis and manipulation. #PythonEfficiency #PandasVectorization #DataManipulation #PythonForDataScience #AvoidForLoops #PythonTips #LargeDatasetsHandling #DataAnalysis #PandasOptimization #PythonCoding #CodingInPython #DataVisualization #DataAnalysis #ai #promptengineering #genai </video> <video> Python Pandas | Video 5 | Part 2 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1Ll4R7lZSp3_5Yi3wyFscGLndspAYrYYW Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Introduction and Course Overview 00:18 - Filtering Data with Conditions 04:39 - Lab Assignments: Filtering Techniques 06:17 - Subsetting Using Indexing 07:36 - Resetting Index in Pandas 10:06 - How to Rename Columns 12:10 - Adding New Columns from Existing Data 17:03 - Sorting Data in Pandas 18:57 - Multi-Column Sorting Explained 21:10 - Lab Assignment: Sorting Operations 21:34 - Detecting Duplicate Rows 22:54 - How to Remove Duplicates 26:03 - Lab Session: Managing Duplicates 26:37 - Understanding Merging and Joins 28:29 - Performing Inner Joins 29:41 - Exploring Full Outer Joins 30:18 - Left and Right outer Joins 31:13 - Joining on Different Columns 33:37 - Lab Session: Data Join Techniques 34:09 - Preview of Upcoming Topics Learn to efficiently filter and sort data while mastering essential DataFrame operations in Pandas. This tutorial covers resetting and managing indexes, renaming columns, and creating new ones to streamline your data workflows. Gain practical skills in identifying and handling duplicate values, ensuring data integrity for analysis. Dive into merging and joining datasets seamlessly, exploring inner, outer, left, and right joins for comprehensive data manipulation. Perfect for data enthusiasts looking to elevate their Python expertise with Pandas! #Python #Pandas #DataManipulation #DataScience #PythonTutorial #DataAnalysis #DataCleaning #DataJoins #sorting #filtering #duplicate #DataFrameOperations #PythonForDataScience #LearnPandas #CodingInPython #DataVisualization #DataAnalysis #ai #promptengineering #genai </video> <video> Power BI Hands-on Course Description: 🚀 Power BI Introduction | Start your data visualization journey with Power BI! Learn the basics of this powerful tool and transform raw data into meaningful insights. 💡 Ready to dive deeper? Check out our full Power BI playlist for comprehensive learning! 🎯 🎥 Watch the Full Playlist Here: https://www.youtube.com/playlist?list=PL2hXNYim5xvqW59QZ-6VX39AqTvKCoWvs #ai #education #datavisualization #powerbi #datascience #dax #powerquery #promptengineering #dataanalytics #datacleaning #dashboard </video> <video> Machine Learning Hands-on Course Description: 🚀 Machine Learning Basics | Begin your journey into the world of Machine Learning! Learn the foundational concepts and understand how to turn data into intelligent insights. 💡 Ready to level up? Explore our full Machine Learning playlist for in-depth learning and hands-on practice! 🎯 🎥 Watch the Full Playlist Here: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- #ai #education #machinelearning #mlbasics #datascience #datapreprocessing #python #predictivemodeling #dataanalytics #featureengineering #deeplearning </video> <video> Python Pandas | Video 5 | Part 1 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1Ll4R7lZSp3_5Yi3wyFscGLndspAYrYYW Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Welcome to the Course Overview 00:18 - Getting Started with Pandas 00:38 - Accessing Material and Code Files 01:51 - Steps to Import Data from a GitHub File 02:27 - How to Import Local Files in Google Colab 04:36 - Importing Excel Files into Google Colab 05:52 - Exploring Various File Types for Importing 06:44 - Data Overview and Structure 07:08 - Importing SAS Files into Google Colab 07:49 - Datasets and Code Links Shared 09:15 - dataframe.shape() Explained 09:29 - dataframe.info() in Action 09:57 - dataframe.columns() in Depth 10:18 - Exploring dataframe.head() 10:39 - Exploring dataframe.tail() 10:53 - Using dataframe.sample() for Random Rows 12:22 - Lab Session Walkthrough 13:13 - Deep Dive into DataFrame.iloc[] 13:44 - Accessing Rows Specifically 14:38 - Accessing Columns Specifically 15:32 - Combining Rows and Columns Access with iloc[] 16:37 - Exploring DataFrame.loc[] Features 16:57 - Comparing iloc and loc Methods 20:59 - Filter Data Using DataFrame.select_dtypes() 22:29 - Dropping Columns with DataFrame.drop() 24:11 - Lab: Dropping DataFrame Columns 25:45 - Lab Session Summary 26:13 - What's Coming Up Next Master the art of working with data in Google Colab using Pandas with this detailed tutorial. Learn to import files from GitHub, local directories, and various formats like Excel and SAS. Gain insights into analyzing data with essential DataFrame methods such as .shape(), .info(), .columns(), .head(), .tail(), and .sample(). Deepen your knowledge of accessing rows and columns using powerful indexing techniques like iloc[] and loc[] while exploring the differences between the two. Discover how to filter data with select_dtypes() and efficiently drop columns with drop(). Hands-on lab sessions ensure you can apply these concepts to real-world scenarios. This guide is perfect for beginners and intermediate learners eager to enhance their data-handling skills in Python. #PythonProgramming #PandasLibrary #DataAnalysis #GoogleColab #PythonForDataScience #DataFrame #ImportingData #PythonTutorial #DataScienceBasics #MachineLearning #PythonTips #DataWrangling #LearnPandas #CodingInPython #DataVisualization #DataAnalysis #ai #promptengineering #genai </video> <video> Python Conditionals, Loops and Functions| Video 4 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LkqkON6k4QZYIBcE1UxtpDYPQxzGNQd3 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Course Introduction 00:18 - Topics Introduction 00:55 - Basics of if Conditions 04:57 - Exploring if, elif, and else in Depth 08:14 - Lab Work: if and else Scenarios 09:35 - Python for Loop Explained 15:14 - Lab: Practical Examples of for Loops 15:53 - Simplifying Code with List Comprehension 19:28 - Defining Functions: User-Defined Functions in Python 24:40 - Lab Session: Functions in Python 26:14 - Conclusion and Next Learning Goals Master the core Python concepts with this tutorial that dives into conditionals, loops, and functions. Learn how to use if, elif, and else statements to create flexible decision-making logic in your programs. Understand the power of for loops for iterating through data efficiently. Explore how to write user-defined functions to enhance code reusability and organization. Perfect for beginners looking to solidify their programming foundation, this video offers practical insights into essential Python techniques. #PythonProgramming #LearnPython #PythonTutorial #CodingForBeginners #PythonBasics #ifelse #forloop #PythonFunctions #PythonCoding #DataScienceWithPython #CodingSkills #LearnNumPy #DataAnalysis #ai #promptengineering #genai </video> <video> Python NumPy | Video 3 | Part 2 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LTWEn-pSCA8ecvQknaftn1gKbWp7XdM2?authuser=3 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com 00:00 - Overview of the Course 00:17 - Dataset Explanation 02:44 - Array Creation from Dataset 04:13 - Accessing and Using Multiple Variables 11:01 - Array Slicing Basics 16:19 - Techniques for Accessing Random Values 18:31 - Introduction to 2D Arrays 21:23 - Indexing 2D Arrays Effectively 25:28 - Additional Practice Examples 36:05 - Conclusion and What's Next Discover the power of Python for data manipulation in this hands-on tutorial! Learn how to import data into Pandas DataFrames and transform it into arrays using NumPy. Explore slicing, indexing, and reshaping techniques for efficient analysis, and understand the difference between one-dimensional and two-dimensional arrays. Get practical tips for working with local files and cloud platforms like Google Colab, including secure data import and drive mounting. This session covers essential Python commands and indexing methods to handle datasets with precision. Perfect for anyone looking to master data science basics and tackle advanced array operations! #PythonForDataScience #NumPy #Pandas #DataFrames #DataAnalysis #CodingTips #DataManipulation #LearnPython #ScientificComputing #LearnNumPy #DataAnalysis #CodingWithPython #ArraysVsLists #dataanalysis #ai #promptengineering #genai </video> <video> Python NumPy | Video 3 | Part 4 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LTWEn-pSCA8ecvQknaftn1gKbWp7XdM2?authuser=3 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Course Overview 00:17 - Exploring the Random Number Function 01:47 - Generating 30 Random Numbers in Python 03:03 - Understanding Random Normal Distribution 08:53 - How to Reshape Arrays 09:55 - Converting a 1D Array into a 2D Array 10:18 - Explanation of the reshape() Function 14:49 - Creating 2D Arrays Using arange() 16:42 - Flexible Array Reshaping Using -1 21:37 - Rules for Using -1 in Array Reshaping 22:33 - Q&A Session 24:14 - Exploring Aggregate Functions in Arrays 25:20 - Introduction to argmax() and argmin() 31:02 - Wrapping Up the Session 32:09 - What’s Next in the Course Take your Python programming to the next level with this NumPy tutorial on random number generation. Learn how to create single or multiple random values and explore essential statistical distributions like normal and uniform. Master reshaping arrays into organized matrices to handle data efficiently. Discover the role of random numbers in simulations, visualizations, and building data graphs. Perfect for beginners and data science enthusiasts, this tutorial provides practical techniques to simplify complex data tasks using Python’s powerful NumPy library. #Python #DataScience #BooleanIndexing #NumPy #Pandas #PythonProgramming #ArrayManipulation #DataFiltering #PythonTips #CodingSkills #LearnNumPy #DataAnalysis #ai #promptengineering #genai </video> <video> Python Data Structures | Video 2 | Part 2 (List Data Type) | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LCkNoOkMHOgiG6c-vlBo9qHL8CkLkA00#scrollTo=_iOyW0aOdDr0 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 Course Contents Overview 00:17 Importance of Built-in Data Types 00:44 Introduction to Lists 01:31 Steps to Define a List 03:36 Accessing List Elements via Index Slicing 05:03 How to Concatenate Two Lists 06:34 Adding Items Using 'Append' 07:12 Deleting Items Using 'Remove' 10:55 How to Use 'Pop' 12:32 Sorting Items in a List 18:54 Understanding Negative Indexing in Lists 21:24 Practical Examples Using Lists 30:34 Lab Assignment for Your Practice In this video, we cover essential Python data handling techniques, focusing on lists—one of the key structures for data storage and retrieval. You’ll learn to define, access, and manipulate lists with examples using familiar names like Sheldon and Penny, making each function, such as append(), remove(), and pop(), more relatable. We explain positive and negative indexing, so you can efficiently target specific elements. Alongside list management. Practice exercises reinforce concepts, ensuring a strong foundation for more advanced Python programming. #PythonTutorial #PythonLists #DataStructures #ProgrammingBasics #PythonForBeginners #DataAnalysis #PythonDictionary #CodingFundamentals #PythonIndexing #PythonSlicing #PythonBasics #dataanalysis #ai #promptengineering #genai </video> <video> Python NumPy | Video 3 | Part 1 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1LTWEn-pSCA8ecvQknaftn1gKbWp7XdM2?authuser=3 Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Overview: What the Course Covers 00:17 - Getting Started with NumPy 01:53 - Arrays: A Deep Dive 04:58 - Comparing Lists and Arrays 12:53 - Hands-On with 1D Arrays 17:44 - Understanding Attributes of Arrays 20:50 - Conclusion and Next Steps Explore the power of NumPy, the go-to Python library for numerical computations! Perfect for data scientists and machine learning enthusiasts, this video introduces NumPy arrays, essential for storing data and performing fast, efficient calculations. Discover how NumPy simplifies tasks like matrix multiplication, reshaping data, and element-wise operations, outperforming Python lists in speed and functionality. Learn the practical differences between lists and arrays, and why arrays are ideal for mathematical and scientific tasks. #NumPy #PythonProgramming #DataScience #PythonArrays #NumericalComputing #MachineLearning #PythonForBeginners #ScientificComputing #LearnNumPy #DataAnalysis #CodingWithPython #ArraysVsLists #dataanalysis #ai #promptengineering #genai </video> <video> Python Pandas | Video 5 | Part 4 | Python Made Easy Description: Code File: https://colab.research.google.com/drive/1Ll4R7lZSp3_5Yi3wyFscGLndspAYrYYW Access the full playlist Python Made Easy : https://www.youtube.com/playlist?list=PL2hXNYim5xvry-2fg6dL9ClOeO-5mImcc Course Material: https://drive.google.com/drive/folders/1F9lWd6eQgECeG7NI3FDjoLBQm-knoEox?usp=sharing To keep up with the latest updates, join our WhatsApp community: https://chat.whatsapp.com/GidY7xFaFtkJg5OqN2X52k Other Playlists ML: https://www.youtube.com/playlist?list=PL2hXNYim5xvpbtGR1C2dgAGCtdnhrZNJ- DL:https://www.youtube.com/playlist?list=PL2hXNYim5xvp8zQb-vAVxvTzudNiRIkjQ GenAI: https://www.youtube.com/playlist?list=PL2hXNYim5xvop-LH93T2P75Y-09GIyHG6 DV Analytics website: https://dvanalyticsmds.com Chapters 00:00 - Overview of the Course 00:18 - Understanding the Dataset 00:50 - Groupby Analysis Explained 04:15 - Applying Aggregate in Groupby 07:11 - Grouping by Multiple Columns 11:12 - Practical Lab: Groupby 11:53 - Introduction to Cross Tables 14:50 - Using Pivot Tables Effectively 17:44 - Hands-on with Cross Tabs & Pivot Tables 18:50 - Wrapping Up: What’s Next Gain insights into housing data analysis with Python's pandas library. Explore features like square footage, house condition, and number of floors, and leverage the groupby() function to segment data by variables such as bedrooms and bathrooms. Discover trends like price variations across conditions or grades while calculating metrics like mean, min, and max values. Use aggregate() for simultaneous calculations and improve readability with multi-index resets and column renaming. This method simplifies data analysis, offering a user-friendly alternative to SQL for group-by operations, making it ideal for understanding complex datasets. #PythonEfficiency #PandasVectorization #DataManipulation #PythonForDataScience #AvoidForLoops #PythonTips #LargeDatasetsHandling #DataAnalysis #PandasOptimization #PythonCoding #CodingInPython #DataVisualization #DataAnalysis #ai #promptengineering #genai </video>

Contacts and Links

Description

🚀 Corporate Trainer in Data Science, Machine Learning & AI

📚 Author & Educator: Books available worldwide
"Machine Learning and Deep Learning using Python and TensorFlow"
"Practical Business Analytics using SAS"

🌟 Professional Expertise:
With a robust foundation in Data Science, I specialize in transforming complex concepts into actionable knowledge. My journey has been marked by deep involvement in credit risk model building, market response modeling, social media analytics, revenue forecasting, and advanced machine learning techniques.

👩‍🏫 Corporate Training Dynamo:
Having delivered over 200 corporate training sessions and helped more than 5000 students, my experience spans across 25+ esteemed organizations. I am passionate about sharing knowledge and empowering professionals to harness the power of Data Science and AI in their respective fields.

💼 Specializations:
Data Science
Machine Learning
Deep Learning

🔧 Tools of the Trade:
R
Python
SAS

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