GPT-4 for Developers
Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges. Comprehensive exploration of data visualization techniques using popular Python libraries such as Matplotlib and Seaborn. This resource is designed to bridge the gap between theore...
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| Médium: | E-kniha |
| Jazyk: | English |
| Vydavateľské údaje: |
Herndon, VA
Mercury Learning & Information
2024
Mercury Learning and Information |
| Vydanie: | 1 |
| Edícia: | MLI Generative AI Series |
| Predmet: | |
| ISBN: | 1501522485, 9781501522482 |
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| Abstract | Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges. Comprehensive exploration of data visualization techniques using popular Python libraries such as Matplotlib and Seaborn. This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments. The book contains an assortment of Python 3.x code samples that were generated by ChatGPT and GPT-4. Chapter 1 provides an overview of ChatGPT and GPT-4, followed by a chapter which contains Python 3.x code samples for solving various programming tasks in Python. Chapter 3 contains code samples for data visualization, and Chapter 4 contains code samples for linear regression. The final chapter covers visualization with Gen AI (Generative AI) and DALL-E. Companion files with source code and figures are available for downloading. |
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| AbstractList | Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges. Comprehensive exploration of data visualization techniques using popular Python libraries such as Matplotlib and Seaborn. This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments. The book contains an assortment of Python 3.x code samples that were generated by ChatGPT and GPT-4. Chapter 1 provides an overview of ChatGPT and GPT-4, followed by a chapter which contains Python 3.x code samples for solving various programming tasks in Python. Chapter 3 contains code samples for data visualization, and Chapter 4 contains code samples for linear regression. The final chapter covers visualization with Gen AI (Generative AI) and DALL-E. Companion files with source code and figures are available for downloading. |
| Author | Campesato, Oswald |
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| DOI | 10.1515/9781501519024 |
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| Discipline | Computer Science |
| EISBN | 1501519026 9781501519024 9781501519048 1501519042 |
| Edition | 1 |
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| Keywords | data science AI software developers data visualization programming, software developers, data science, Python, artificial intelligence, AI, data visualization programming artificial intelligence Python |
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| PublicationDate | 2024 [2023] |
| PublicationDateYYYYMMDD | 2024-01-01 2023-01-01 |
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| PublicationDecade | 2020 |
| PublicationPlace | Herndon, VA |
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| PublicationSeriesTitle | MLI Generative AI Series |
| PublicationYear | 2024 2023 |
| Publisher | Mercury Learning & Information Mercury Learning and Information |
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| Snippet | Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges. Comprehensive exploration of data... |
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| SubjectTerms | artificial intelligence ChatGPT COM004000 COMPUTERS / Intelligence (AI) & Semantics COMPUTERS / Programming / General COMPUTERS / Programming Languages / Python data science data visualization Natural language generation (Computer science)-Computer programs programming programming, software developers, data science, Python, artificial intelligence, AI, data visualization Python software developers Web applications-Development |
| TableOfContents | Codex (OpenAI) -- Apple GPT -- PaLM-2 -- Med-PaLM M -- Claude 2 -- LlaMa-2 -- How to Download LlaMa-2 -- LlaMa-2 Architecture Features -- Fine-Tuning LlaMa-2 -- When is GPT-5 Available? -- Summary -- Chapter 2: ChatGPT and Python -- Simple Calculator -- Simple File Handling -- Simple Web Scraping -- Basic Chatbot -- Basic Data Visualization -- Basic Pandas -- Generate Random Data -- Recursion: Fibonacci Numbers -- Object Oriented Programming -- Asynchronous Programming with asyncio -- Working with Requests in Python -- Image Processing with PIL -- Exception Handling -- Generators in Python -- Roll 7 or 11 with Two Dice -- Roll 7 or 11 with Three Dice -- Roll 7 or 11 with Four Dice -- Mean and Standard Deviation -- Summary -- Chapter 3: ChatGPT and Data Visualization -- Working with Charts and Graphs -- Bar Charts -- Pie Charts -- Line Graphs -- Heat Maps -- Histograms -- Box Plots -- Pareto Charts -- Radar Charts -- Treemaps -- Waterfall Charts -- Line Plots with Matplotlib -- A Pie Chart Using Matplotlib -- Box-and-Whisker Plots using Matplotlib -- Time Series Visualization with Matplotlib -- Stacked Bar Charts with Matplotlib -- Donut Charts Using Matplotlib -- 3D Surface Plots with Matplotlib -- Radial or Spider Charts with Matplotlib -- Matplotlib's Contour Plots -- Stream Plots for Vector Fields -- Quiver Plots for Vector Fields -- Polar Plots -- Bar Charts with Seaborn -- Scatter Plots with Regression Lines Using Seaborn -- Heatmaps for a Correlation Matrix with Seaborn -- Histograms with Seaborn -- Violin Plots with Seaborn -- Pair Plots Using Seaborn -- Facet Grids with Seaborn -- Hierarchical Clustering -- Swarm Plots -- Joint Plots for Bivariate Data -- Point Plots for Factorized Views -- Seaborn's KDE Plots for Density Estimations -- Seaborn's Ridge Plots -- Summary -- Chapter 4: Linear Regression With GPT-4 -- What is Linear Regression? Examples of Linear Regression -- Metrics for Linear Regression -- Coefficient of Determination (R2) -- Linear Regression with Random Data with GPT-4 -- Linear Regression with a Dataset with GPT-4 -- Describe the Features of the death.csv Dataset -- The Preparation Process of the Dataset -- The Exploratory Analysis -- Detailed EDA on the death.csv Dataset -- Bivariate and Multivariate Analyses -- The Model Selection Process -- Code for Linear Regression with the death.csv Dataset -- Describe the Model Diagnostics -- Additional Model Diagnostics -- More Recommendations from GPT-4 -- Summary -- Chapter 5: Visualization with Generative AI -- Generative AI and Art and Copyrights -- Generative AI and GANs -- GANs (Generative Adversarial Networks) -- What is Diffusion? -- Diffusion Image Sample -- Diffusion Models Versus GANs -- What are Diffusers and DDPMs? -- CLIP (OpenAI) -- GLIDE (OpenAI) -- Text-to-Image Generation -- Stability AI/Stable Diffusion -- Imagen (Google) -- Make-a-Scene (Meta) -- Diffuse the Rest -- GauGAN2 (NVIDIA) -- PromptBase -- Limitations of Text-to-Image Models -- Text-to-Image Models -- The DALL-E Models -- DALL-E -- DALL-E 3 -- Paid Accounts for DALL-E -- Invoking the DALL-E API -- DALL-E 2 -- DALL-E 2 Overview -- The DALL-E 2 Model -- DALL-E 2 Content Preparation -- DALL-E-Bot -- DALL-E Demos -- Text-to-Video Generation -- Meta (Make-a-Video) -- Imagen Text-to-Video -- Ruben Villegas and Google (Phenaki) -- Text-to-Speech Generation -- Whisper (OpenAI) -- Summary -- Index Cover -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Chapter 1: ChatGPT and GPT-4 -- What is Generative AI? -- Key Features of Generative AI -- Popular Techniques in Generative AI -- What Makes Generative AI Different -- Conversational AI Versus Generative AI -- Primary Objectives -- Applications -- Technologies Used -- Training and Interaction -- Evaluation -- Data Requirements -- Is DALL-E Part of Generative AI? -- Are ChatGPT-3 and GPT-4 Part of Generative AI? -- DeepMind -- DeepMind and Games -- Player of Games (PoG) -- OpenAI -- Cohere -- Hugging Face -- Hugging Face Libraries -- Hugging Face Model Hub -- AI21 -- InflectionAI -- Anthropic -- What is Prompt Engineering? -- Prompts and Completions -- Types of Prompts -- Instruction Prompts -- Reverse Prompts -- System Prompts Versus Agent Prompts -- Prompt Templates -- Prompts for Different LLMs -- Poorly Worded Prompts -- What is ChatGPT? -- ChatGPT: GPT-3 "on Steroids?" -- ChatGPT: Google "Code Red" -- ChatGPT Versus Google Search -- ChatGPT Custom Instructions -- ChatGPT on Mobile Devices and Browsers -- ChatGPT and Prompts -- GPTBot -- ChatGPT Playground -- ChatGPT and Medical Diagnosis -- Plugins, Advanced Data Analysis, and Code Whisperer -- Plugins -- Advanced Data Analysis -- Advanced Data Analysis Versus Claude 2 -- Code Whisperer -- Detecting Generated Text -- Concerns About ChatGPT -- Code Generation and Dangerous Topics -- ChatGPT Strengths and Weaknesses -- Sample Queries and Responses from ChatGPT -- Alternatives to ChatGPT -- Google Bard -- YouChat -- Pi from Inflection -- Machine Learning and ChatGPT: Advanced Data Analysis -- What is InstructGPT? -- VizGPT and Data Visualization -- What is GPT-4? -- GPT-4 and Test-Taking Scores -- GPT-4 Parameters -- GPT-4 Fine-Tuning -- ChatGPT and GPT-4 Competitors -- Bard -- CoPilot (OpenAI/Microsoft) Chapter 5: Visualization with Generative AI -- Contents -- Chapter 2: ChatGPT and Python -- Preface -- Frontmatter -- Chapter 1: ChatGPT and GPT-4 -- Index Chapter 3: ChatGPT and Data Visualization -- Chapter 4: Linear Regression With GPT-4 -- |
| Title | GPT-4 for Developers |
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