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Note - Read entire description before you purchase the package. This package offers a diverse range of projects covering 10 Excel Projects on various domains, providing hands-on experience with different functionalities, Date & Time functions, Logical Functions, Conditional Formatting's, Pivot Tables, Calculated Fields & Items, Pivot Charts, chart types, data modeling, and data cleaning techniques. Each project comes with its own set of resources including the tableau file, raw data, problem statement, background uses, PowerPoint presentations, and images used in the project. Here's a brief overview of the projects included in the package: Bank Loan Project: Analyzing bank loan data in the finance domain. Aviation Accident Analysis: Insights into Aviation Accidents. Chicago Crime Analysis : Analyze how Chicago Crime are increasing day by day. Road Accidents (3 Dashboards): Analyzing Road accidents in 3 different dashboards for different Factors Electric Vehicle Report: Analyzing data related to electric vehicles in the manufacturing domain. HR Analytics: Analyzing human resources data. Pizza Sales Analysis: Insights into service and sales in the food industry. Ecommerce Sales Analysis: Understanding supply chain dynamics in e-commerce. IPL Analysis: Analysis of IPL Matches Website Sales Analysis: Analysis of Sales done in India These projects offer valuable learning opportunities and can enhance resumes by showcasing proficiency in Excel across different domains. Users can work on these projects independently, leveraging the provided resources to apply their learnings, enhance their capabilities, and prepare for interviews. Inclusions/ Exclusions in Package Dashboard Excel File Raw Data in Same File Problem Statement Background Used Images Used No video or documented explanations of projects available Note: The Material / Projects do not have Video Explanation Steps. They contain first 5 inclusions only. For further inquiries or assistance, users can contact the provider. Email - [email protected] WhatsApp - +91 9579005495

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Introduction to PyTorch fundamentals, covering tensor initialization, operations, indexing, and reshaping. ✅ What are Tensors? ✅ Tensor Initialization ✅ Common Tensor Initialization Methods ✅ Tensor Type Conversion ✅ Converting Between NumPy Arrays and Tensors ✅ Tensor Mathematics and Comparison Operations ✅ Matrix Multiplication and Batch Operations ✅ Broadcasting and Other Useful Operations ✅ Tensor Indexing ✅ Tensor Reshaping

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Learning a language is easy. Whenever I start with a new language, I focus on a few things like operations and loops common to every language, and it is a breeze to get started with writing code in any language. However, learning to write code in a language and writing a language in an optimized way are two different things. Every Language has some ingredients which make it unique. Yet, a new programmer to any language will always do some forced overfitting. In this book, I will explain some simple constructs provided by Python, some essential tips, and some use cases I come up with regularly in my Data Science work. Most of the book is of a practical nature and you will find it beaming with examples. And the best thing- It's FREE, and you can choose to pay only if you like it. TOC: Chapter 1: Minimize for loop usage in Python (List Comprehensions) Chapter 2: Python defaultdict and Counter Chapter 3: *args, **kwargs, decorators for Data Scientists Chapter 4: Use Iterators, Generators, and Generator Expressions Chapter 5: How and Why to use f strings in Python3? Chapter 6: Object Oriented Programming Chapter 7: Dunder Methods Chapter 8: Regexes Everywhere!!! Chapter 9: Type Annotations with Python Here is a review:

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👁️ Computer Networking Handwritten Notes 📘 Important Topics for Data Communication and Networking Following are important topics for final exam of DCN: [Kindly mention in comment if some topic is missing] Error Detection and Error Correction LAN Addresses and Address Resolution Protocol IP Datagram Format IP Addressing Subnetting and Variable Length Subnet Mask Graph Abstraction Multicast vs Broadcast TCP/UDP TCP Flow Control Slow Start HTTP (Persistent vs Non-Persistent) DNS QoS