Data Science Interview Mastery 200 Generative Ai Deep Learning Nlp Q A To Ace Your Next Tech Interview


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Data Science Interview Mastery: 200+ Generative AI, Deep Learning & NLP Q&A to Ace Your Next Tech Interview


Data Science Interview Mastery: 200+ Generative AI, Deep Learning & NLP Q&A to Ace Your Next Tech Interview

Author: Ravi Kiran

language: en

Publisher: Ravi Kiran

Release Date:


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🚀 Master Your Next Data Science Interview with Generative AI, Deep Learning & NLP Expertise! Are you preparing for a data science, machine learning, or AI interview at top tech companies like FAANG, Microsoft, or cutting-edge startups? This book is your ultimate weapon to tackle the toughest questions on Generative AI, Deep Learning, and Natural Language Processing (NLP)—all in one place! 🔥 What’s Inside? ✔ 200+ Real Interview Questions – Carefully curated from top tech companies and industry trends. ✔ In-Depth Answers – Clear, concise, and expert-backed explanations to boost your confidence. ✔ Generative AI Focus – Master LLMs (GPT, Gemini, Claude), Diffusion Models, RAG, and Fine-Tuning. ✔ Deep Learning & NLP Deep Dive – Convolutional Networks (CNNs), Transformers, BERT, Attention Mechanisms, and more! ✔ FAANG & Big Tech Ready – Questions patterned after Google, Meta, OpenAI, and AI research labs. ✔ Practical Coding & Theory – Balance between conceptual understanding and hands-on implementation. 🎯 Who Is This Book For? Aspiring Data Scientists & ML Engineers prepping for interviews. AI Researchers & NLP Specialists expanding their knowledge. Tech Professionals transitioning into Generative AI & Deep Learning roles. Computer Science Students preparing for campus placements & internships. 💡 Why Choose This Guide? ✅ Up-to-date with 2024 AI trends – Covers the latest in ChatGPT, LangChain, Vector DBs, and MLOps. ✅ Structured Learning Path – From fundamentals to advanced system design & case studies. ✅ Proven Success – Designed by industry experts who’ve aced and conducted top-tier interviews. 📈 Don’t Leave Your Dream Job to Chance—Prepare Like a Pro! Grab your copy now and CRACK your next Data Science & AI Interview with confidence!

Deep Learning with Python


Deep Learning with Python

Author: Francois Chollet

language: en

Publisher: Simon and Schuster

Release Date: 2017-11-30


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Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

The Robotic Process Automation Handbook


The Robotic Process Automation Handbook

Author: Tom Taulli

language: en

Publisher: Apress

Release Date: 2020-02-28


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While Robotic Process Automation (RPA) has been around for about 20 years, it has hit an inflection point because of the convergence of cloud computing, big data and AI. This book shows you how to leverage RPA effectively in your company to automate repetitive and rules-based processes, such as scheduling, inputting/transferring data, cut and paste, filling out forms, and search. Using practical aspects of implementing the technology (based on case studies and industry best practices), you’ll see how companies have been able to realize substantial ROI (Return On Investment) with their implementations, such as by lessening the need for hiring or outsourcing. By understanding the core concepts of RPA, you’ll also see that the technology significantly increases compliance – leading to fewer issues with regulations – and minimizes costly errors. RPA software revenues have recently soared by over 60 percent, which is the fastest ramp in the tech industry, and they are expected to exceed $1 billion by the end of 2019. It is generally seamless with legacy IT environments, making it easier for companies to pursue a strategy of digital transformation and can even be a gateway to AI. The Robotic Process Automation Handbook puts everything you need to know into one place to be a part of this wave. What You'll Learn Develop the right strategy and plan Deal with resistance and fears from employees Take an in-depth look at the leading RPA systems, including where they are most effective, the risks and the costs Evaluate an RPA system Who This Book Is For IT specialists and managers at mid-to-large companies