🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 will talk about multiple use cases where you can use ChatGPT. There are several day to day applications where you can leverage ChatGPT to do the job for you. Below are some important ChatGPT applications covered in this ChatGPT tutorial:
00:00:00 Introduction
00:00:50 ChatGPT for Writing Code
00:02:25 ChatGPT for Code Debugging
00:03:37 ChatGPT for Content Writing
00:05:03 ChatGPT for SEO
00:06:18 ChatGPT for Language Translation
00:07:01 ChatGPT for Writing Legal Documents
00:08:11 ChatGPT for College Assignments
00:08:37 ChatGPT to make Workout Schedule

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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
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Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 will talk about multiple use cases where you can use ChatGPT. There are several day to day applications where you can leverage ChatGPT to do the job for you. Below are some important ChatGPT applications covered in this ChatGPT tutorial:
00:00:00 Introduction
00:00:50 ChatGPT for Writing Code
00:02:25 ChatGPT for Code Debugging
00:03:37 ChatGPT for Content Writing
00:05:03 ChatGPT for SEO
00:06:18 ChatGPT for Language Translation
00:07:01 ChatGPT for Writing Legal Documents
00:08:11 ChatGPT for College Assignments
00:08:37 ChatGPT to make Workout Schedule

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

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🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh


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📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
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📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

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Welcome to the Tutorial on Prompt Library, your comprehensive toolkit for mastering myriad use cases with ease. Whether you're delving into programming, honing creative writing skills, or exploring data analysis, this library offers a versatile array of prompts tailored to your needs. Seamlessly designed to inspire, instruct, and elevate your learning experience, each prompt is crafted with precision to ignite creativity and foster skill development. Join in as we deep dive into this tutorial

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

#PromptEngineeringTutorialForBeginners #WhatIsPromptEngineering #IntroductionToPromptEngineering #PromptEngineering #PromptEngineeringIntroduction #PromptEngineeringChatGPT #PromptEngineeringTutorial #AIML #MachineLearning #ML #ArtificialIntelligence #AI #Simplilearn

➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
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- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

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Welcome to our comprehensive "Prompt Engineering Full Course," where you'll explore the fascinating world of prompt engineering and its extensive applications in AI technology. This ChatGPT Prompt Engineering Course in-depth tutorial is meticulously designed to help you master the art of crafting effective prompts, an essential skill for anyone working with AI models. We will start with the basics, understanding what prompt engineering is and why it is crucial in the realm of AI. Discover the numerous ways prompt engineering can be applied across various industries. From content creation and SEO to software development, data analysis, education, legal compliance, and customer support, this course provides real-world examples to illustrate the power and versatility of well-crafted prompts. Gain a deeper understanding of advanced topics such as tokenization, the ChatGPT memory feature, and how to customize GPT-4 for specific tasks. We’ll guide you step-by-step through crafting prompts for different use cases, providing detailed examples and DIY exercises to enhance your skills.

00:00:00 Introduction to Prompt Engineering
00:02:29 What is Prompt Engineering
00:03:11 Crafting Effective Prompts
00:04:04 Practical Examples Writing Effective Prompts
00:05:19 Exploring Prompt Engineering Use Cases in Various Sectors
00:07:09 Flow of AI Technologies
00:08:27 having an Overview of Openai and ChatGPT
00:10:28 Tokenization in ChatGPT
00:12:29 Exploring Customize ChatGPT Feature
00:13:26 Exploring GPT 4o and Temporary chat Section
00:13:40 Components required to craft an Effective Prompt
00:16:50 Exploring Prompts with Examples
00:21:56 Examples for crafting Prompts for various Use Cases
00:22:00 Crafting Prompt for Content Creation
00:25:34 Crafting Prompt for SEO Optimization
00:28:40 Crafting Prompt for Developers or Development Field
00:33:20 Crafting Prompt for Data Analysis
00:38:03 Crafting Prompt for Educational Purpose or Roadmaps
00:41:43 Crafting Prompt for Legal and Compliance Field
00:46:29 Crafting Prompt for Customer Support
00:53:50 Exploring ChatGPT's Memory Feature

✅What does prompt engineering do?
Prompt engineering involves crafting effective and specific prompts to guide AI models like ChatGPT in generating desired responses.

✅What is the salary for prompt engineering?
Salaries for prompt engineering can vary based on factors such as location, experience, and the specific industry.

✅What is prompt engineering in ChatGPT?
In ChatGPT, prompt engineering refers to the process of designing prompts or inputs that influence the responses generated by the model.

#PromptEngineering #AI #MachineLearning #ChatGPT #GenerativeAI #ArtificialIntelligence #2024 #Simplilearn #TechTraining

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➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.

IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

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- Add the IBM Advantage to your Learning
- 25 Industry-relevant Projects and Integrated labs
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✅ Inspiring Success Stories of Simplilearn's Learners: https://www.simplilearn.com/reviews?utm_campaign=7June24PromptEngineeringFC&utm_medium=Description&utm_source=youtube

Learn more about watsonx: https://ibm.biz/BdvxDS

What is really the difference between Artificial intelligence (AI) and machine learning (ML)? Are they actually the same thing? In this video, Jeff Crume explains the differences and relationship between AI & ML, as well as how related topics like Deep Learning (DL) and other types and properties of each.

#ai #ml #dl #artificialintelligence #machinelearning #deeplearning #watsonx

TensorFlow is a tool for machine learning capable of building deep neural networks with high-level Python code. It provides developer-friendly APIs that help software engineers train, analyze, and deploy ML models.

#programming #deeplearning #100secondsofcode

🔗 Resources

TensorFlow Docs https://www.tensorflow.org/
Fashion MNIST Tutorial https://www.tensorflow.org/tutorials/keras/classification
Neural Networks Overview for Data Scientists https://www.ibm.com/cloud/learn/neural-networks
Machine Learning in 100 Seconds https://youtu.be/PeMlggyqz0Y

🔥 Get More Content - Upgrade to PRO

Upgrade to Fireship PRO at https://fireship.io/pro
Use code lORhwXd2 for 25% off your first payment.

🎨 My Editor Settings

- Atom One Dark
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🔖 Topics Covered

- What is TensorFlow?
- How to build a neural network with TensorFlow
- What is TensorFlow used for?
- Who created TensorFlow?
- How neural networks work
- Easy neural network tutorial
- What is a mathematical Tensor?

In this video, we see two math problems that require the exact same logic to solve. However, one is very easy and one is very hard. Why?

For information on my book "Grokking Machine Learning":
https://www.manning.com/books/....grokking-machine-lea
Discount code (40%): serranoyt

This video is about the Fast Fourier Transform.

This is the third in a series of videos about Fourier transforms.

- First video: The Discrete Fourier Transform https://www.youtube.com/watch?v=T8XZxR5H04E
- Second video: Detecting Periodicity with the DFT https://youtu.be/bk9VGJNzQM0
- Third video: The Fast Fourier Transform (this one)

Grokking Machine Learning Book:
https://www.manning.com/books/....grokking-machine-lea
40% discount promo code: serranoyt

00:00 Introduction
00:27 The Discrete Fourier Transform
03:01 The Fast Fourier Transform
07:28 The Butterfly

Highlight: At 33:30 Josh Starmer, Statsquatch, and the Normalsaurus from @statquest have an awesome cameo!

A video about autoencoders, a very powerful generative model. The video includes:
Intro: (0:25)
Dimensionality reduction (3:35)
Denoising autoencoders (10:50)
Variational autoencoders (18:15)
Training autoencoders (23:36)

Github repo: www.github.com/luisguiserrano/autoencoders

Recommended videos:
Generative adversarial networks: https://www.youtube.com/watch?v=8L11aMN5KY8
Restricted Boltzmann machines: https://www.youtube.com/watch?v=Fkw0_aAtwIw
Matrix factorization: https://www.youtube.com/watch?v=ZspR5PZemcs
Singular value decomposition: https://www.youtube.com/watch?v=DG7YTlGnCEo
Neural networks: https://www.youtube.com/watch?v=BR9h47Jtqyw
Convolutional neural networks: https://www.youtube.com/watch?v=2-Ol7ZB0MmU
Recurrent neural networks: https://www.youtube.com/watch?v=2-Ol7ZB0MmU
Logistic regression: https://www.youtube.com/watch?v=jbluHIgBmBo
Shannon entropy: https://www.youtube.com/watch?v=9r7FIXEAGvs

Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

0:00 Introduction
0:13 Generative models
3:03 Variational autoencoders
3:45 Dataset of images
10:16 Denoising autoencoders
10:27 Linear methods
10:53 A friendly introduction to deep learning and neural networks
11:58 Mapping the real numbers to the interval (0,1)
12:23 Sigmoid function
12:41 Perceptron
15:02 Correct noise
18:20 Autoencoders as generators
20:16 Latent space
23:41 Training a neural network - loss function
25:18 Training an autoencoder
25:32 Training autoencoders
25:46 Reconstruction loss (Mean squared error)
26:31 Reconstruction loss (log-loss)
27:11 Training a variational auto encoder

Correction: At 30:05, the number in the middle of the red graph should be 0.4, not 0.3.

CORRECTION: at 13:41, the probability is 6.1e-5 and not 4.8e-4 (however, the entropy is 1.75, which is correct). Thank you @dlyChimi!

Learn Shannon entropy and information gain by playing a game consisting in picking colored balls from buckets.

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

Accompanying blog post: https://medium.com/p/5810d35d54b4/

0:00 Shannon Entropy and Information Gain
2:22 What ball will we pick?
4:33 Quiz
5:06 Question
5:14 Game
7:17 Probability of Winning
7:45 Products
11:00 What if there are more classes?
12:34 Sequence 2
13:44 Sequence 3
14:57 Naive Approach
15:34 Sequence 1
19:44 General Formula

Correction (10:26). The probabilities are wrong. The correct ones are here:
For Die 1: 0.4^4 * 0.2^2 * 0.1^1 * 0.1^1 * 0.2^2
For Die 2: 0.4^4 * 0.1^2 * 0.2^1 * 0.2^1 * 0.1^2
For Die 3: 0.1^4 * 0.2^2 * 0.4^1 * 0.2^1 * 0.1^2

Kullback Leibler (KL) divergence is a way to measure how far apart two distributions are.
In this video, we learn KL-divergence in a simple way, using a probability game with dice.

Shannon entropy and information gain: https://www.youtube.com/watch?v=9r7FIXEAGvs&t=1066s&pp=ygUic2hhbm5vbiBlbnRyb3B5IGluZm9ybWF0aW9uIHRoZW9yeQ%3D%3D

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Today we're diving deep into one of the hottest topics in AI right now. Building actual agents in Python. Not just chat bots to respond to your queries, but autonomous systems with memory goals and the ability to take actions in the world.

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⏳ Timestamps ⏳
00:00 | AI Agents
00:37 | NVIDIA Free AI Courses
01:38 | AI Agent Building Blocks
05:30 | Python Frameworks
09:01 | Python Tools
09:40 | AI Agent Patterns
13:15 | Picking Your Stack

Hashtags
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Hi my name is Chris and I build productivity apps 👋 and this is EVERYTHING I learned building an AI agent using the Anthropic Agent SDK :)

---
Check out Convex (database I'm using): https://convex.link/chrisraroque
(please tell them I sent you 🙏)
---

My apps and socials: https://chrisraroque.com
My agency (work with me): https://aloa.co/

Timestamps:
0:00 – Intro / What we are covering
1:03 - What I built with the Agent SDK
2:28 - How Agents Work & Agent SDK Bascs
4:50 - What makes the Agent SDK special
7:55 - Using Convex as the database for my agent
9:19 - Building tools for the agent
10:28 - Agent Skills
12:32 - Agent memory
14:24 - Why I could not release my agent
17:07 - Practical use cases for agents
18:26 - Deploying agents
19:47 - Final thoughts and thank you :)

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Build Your First AI Agent In 15 Minutes (No Coding). Join our FREE community with all our prompts: https://www.skool.com/ai-launchpad/about

Chatling (FREE Trial): https://chatling.ai/

Chapters:
0:00 - Intro
1:47 - Setup Chatling
2:45 - Configure your agent
5:00 - Add knowledge base + data sources
6:49 - Configure actions
11:28 - Testing in playground
13:40 - Deploy to website
15:55 - Deploy to instagram
17:16 - Outro


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business@zinhomedia.com

Build your first AI agent without coding, check out Lindy: https://go.lindy.ai/ishan

In the past few months, the internet has been flooded with articles and videos about AI agents, highlighting how they simplify people's lives, maximize productivity, and even generate income.

I finally found a crazy AI tool that can help you build AI agents by just describing your idea through a simple text prompt. It has more than 1000 integrations, and it works with all your daily apps like Gmail, Google Calendar, Notion, Sheets, and even social media apps.

From email replier, meeting summariser, AI grammar assistant, to even writing social media posts for you, you can build agents for anything

It has lots of ready-to-use templates that you can try out and start building for free

The smartest people I know are already using AI agents like this to free up their time.

Watch the video till the end to learn about it in detail, and let me know in the comments what you are going to build with Lindy

📸 Instagram: https://bit.ly/ishansharma7390ig

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CHAPTERS:-
00:00 - Introduction
01:34 - Lindy interface
02:06 - Flow editor
09:51 - AI agent
11:38 - Examples of AI agents
15:49 - Conclusion

😁 About Me: https://bit.ly/aboutishansharma
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✨ Hashtags ✨
#ai #artificialintelligence #aiagents