🔥Edureka's Data Science Training: https://www.edureka.co/data-sc....ience-python-certifi
This Edureka video on 'Support Vector Machine Tutorial For Beginners' covers A brief introduction to Support Vector Machine in Python with a use case to implement SVM using Python.
Topics covered in this video:
00:00:00 Introduction
00:01:15 Agenda
00:01:54 What is Machine Learning?
00:05:37 What is Support Vector Machine?
00:06:51 How does SVM work?
00:09:06 SVM Kernels
00:14:16 SVM Usecases
00:14:33 How to implement SVM
00:14:50 Hands-on

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#edureka #datascienceedureka #SupportVectorMachine #SVM #DataScience #MachineLearning #MachineLearningTraining #learnMachineLearning #withme

----------------------------------------
About the Course :

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.
--------------------------------------
Why Learn Machine Learning with Python?

Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
--------------------------------------------
Who should go for this Course?

Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models
--------------------------------
Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.
For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Dr. Matthew Lungren presents labeling work using deep learning at the NIH AI Radiology workshop 2018

There is so much being said about artificial intelligence these days. In order to understand this latest wave of AI, it is important to know how it works and why this moment is different from developments in the past.

WSJ science reporter Eric Niiler joins host Zoe Thomas for the first installment of Tech News Briefing’s special series Artificially Minded. New episodes drop every Monday in April.

0:00 AI basics
2:18 What is machine learning?
4:20 How generative AI like ChatGPT works
6:07 AI in our daily lives
7:45 How people on the street feel about AI
8:38 Why AI is a hot topic right now
9:50 Risks and rules surrounding AI

Tech News Briefing
WSJ’s tech podcast featuring breaking news, scoops and tips on tech innovations and policy debates, plus exclusive interviews with movers and shakers in the industry.

For more episodes of WSJ’s Tech News Briefing: https://link.chtbl.com/WSJTechNewsBriefing

#AI #ArtificialIntelligence #WSJ

A quick walkthrough of training a fine-tuned model on gpt-3 using the openai cli.

In this video I train a fine-tuned gpt-3 model on Radiohead lyrics so that it will generate a Radiohead song form the first line.

Documentation: https://beta.openai.com/docs/guides/fine-tuning

I'm going to show you GPT3 playground and how I built my very first GPT3 based application. GPT3 is amazing and this tutorial will take you into the magic and give you the basics of prompt design and examples of how the tech can be applied in python.

I've made the Google Colab and Github repos available here:

Google Colab notebook example:
https://colab.research.google.....com/drive/1TyuTvjs0h

Github Cbot command line example
https://github.com/graiz/cbot

Blog post with additional details:
https://gregraiz.com/building-....a-command-line-appli

How do you get an API key?
You have to apply for a key on OpenAI: https://beta.openai.com/
If you're waiting you can play around with GPT2. I have a video on how that works here: https://www.youtube.com/watch?v=R6KoIp1ETpM

Follow me on twitter http://www.twitter.com/graiz
I also have a blog and discord channel if you want to connect with me:
https://www.gregraiz.com

- GPT 3 demo of how to use the Open AI playground
- GPT 3 demo of using Google Colab with OpenAI
- GPT 3 demo of exporting an app to Python
- GPT 3 demo some of the problems with Open AI
- GPT3 demo of command line auto-complete from English to shell commands

The entire experience of building a GPT3 application is incredibly easy. That being said there are a lot of limits on what GPT3 currently does.

The core of the GPT3 experience is a single screen called the playground, this is where you can send commands, adjust the sliders and settings and see responses. The rest of the interface is example prompts that fill-in data from the playground and documentation.

The core of GPT3 is that it's a very sophisticated auto-complete. So when designing a prompt or playing with the playground, you want to give it as much context to complete your text in a meaningful way.

After playing around in the playground, I wanted to build an actual app that I could use on a regular basis. I've been trying to use the command line more to keep my hands on the keyboard and keep from dragging/dropping files around but I would often forget the more obscure commands.

I decided to build a bot that would help me find those commands based on simple english querries like.
- How do you install a program
- How do you change permissions on a file
- How do you copy files or pretty much anything else.

I started in the playground and got a very basic version working. OpenAi gives you tools to export the code and I did that into Google Collab. This is an interactive way to run/test and edit python. This was my first python program I've written so the interactive nature was helpful in playing around with basic concepts and getting the bare bones of the program running.

From there I was able to copy the code to my computer and get it working even better. I made this utility that I call cbot, I've made it open source and available to try. Unfortunately you do need an OpenAI API key to use it. This is unfortunate because it makes it difficult for developers to create and share open source tools that leverage OpenAI.

So far cbot has been really useful for looking up obscure commands and allows me to stay in the flow rather than jumping around the web trying to look up commands. My big takeaways from building my first GPT3 application:

1 - Getting started is incredibly easy and a lot of fun. I played around with how AI could be applied to ordering systems, explaining medicines in plain english to patients, grammar correction, and authoring Seinfeld fan-fiction scripts. I'm excited because there's a lot of interesting applications and the technology is very accessible.
2 - It's not magic and it's not perfect. It would often go off on a tangent and occasionally get stuck in a loop. There are controls to adjust how it will perform, but tweeking these controls seems to be an art, not a science.
3 - Developers should think of OpenAI as infrastructure. Similar to AWS, or Azure, it's providing pieces of functionality for your product/application. It's also a dependency and a point of failure. If you're starting a business using GPT3 you need to consider your long-term advantage and moat for your company because application of this technology will become common place.
4 - After playing with GPT3, I'm less concerned about the tech becoming self-aware and taking over the world. It's really impressive but it still has a long way to go. As I said before, the PT in GPT stands for pre-training and in the current version you're not yet able to upload large sets of data to fine tune the model. This is something that OpenAI is working on but it's got a way to go.
5 - Lastly - We are at the very start of something really big. If someone with no prior python experience can whip together an app that harnesses the collective knowledge of the web, just imagine where the technology can go.

Just a few years ago, state-of-the-art, autoregressive natural language processing models had 100 million parameters and we thought that was massive. Now, Cerebras makes it not just possible, but easy, to continuously train and fine-tune the powerful open source GPT-J model with six billion parameters on a single CS-2 system using our groundbreaking weight streaming execution mode.

Learn more: https://www.cerebras.net/blog/....cerebras-makes-it-ea

#ai #deeplearning #GPTJ #artificialintelligence #NLP #naturallanguageprocessing

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐍𝐨𝐝𝐞.𝐣𝐬 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 : https://www.edureka.co/nodejs-....certification-traini (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka "Introduction to Node.js" video will help you to learn the Node.js fundamentals and how to create an application in Node.js. Node.js is an open-source, cross-platform JavaScript runtime environment for developing a diverse variety of server tools and applications.

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

🔵 Welcome to this Edureka video on 𝐇𝐨𝐰 𝐭𝐨 𝐮𝐬𝐞 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 tutorial. 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 has got people going nuts! This NLP breakthrough has been redefining chatbots and its applications. This "How to use 𝐂𝐡𝐚𝐭𝐆𝐏𝐓" video will give you a brief introduction to how you can get started using 𝐂𝐡𝐚𝐭𝐆𝐏𝐓. The Chat GPT explanation given in this Chat GPT Tutorial is ideal for both beginners and advanced IT professionals. Below are the topics explained this 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 Tutorial video:

00:00 Chat GPT Explained
01:03 What is Chat GPT
01:53 Risks of Chat GPT
02:26 How to use Chat GPT
03:03 ChatGPT for Coding
03:47 Make a Shopping List using ChatGPT
05:30 Conclusion

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou

⏩ Edureka Chat GPT Explained Playlist: http://bit.ly/3HGRy3G

🔵 If you want a more comprehensive tutorial, you can find it over here: https://youtu.be/fuJZUadO4po

🔵 You can access OpenAI ChatGPT signup here:
https://chat.openai.com/

🔵 I’ve also added the link for DALL-E 2 if you’re interested:
https://openai.com/dall-e-2/

#howtousechatgpt #edureka #chatgptexplained #chatgpt #openai #chatgpttutorial #chatgpt3

Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

🔵 Artificial and Machine Learning PGD with E&ICT Academy
NIT Warangal: http://bit.ly/3OuZ3xs

🌕 Professional Certificate 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

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 2023 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

🔵 About Edureka ChatGPT Certification Training Course

Edureka’s ChatGPT Certification Training Course will teach you about ChatGPT architecture, GPT models, methodology, and real-world applications. The ChatGPT certification training program is an excellent choice for individuals and organizations seeking to improve their language processing and AI skills and knowledge.

🔵 Why take up the Online ChatGPT Certification Course?

Interested individuals can opt for the Online ChatGPT Certification course as this course provides:

Comprehensive knowledge: The course provides a comprehensive understanding of ChatGPT, including its architecture, training methodology, and real-world applications.

Career advancement: The certification demonstrates an individual's expertise and competence in working with ChatGPT, making them a valuable asset to any organization.

Stay ahead of the curve: ChatGPT is a rapidly growing field, and with the certification, one can stay ahead of the curve and stay updated with the latest advancements in the industry.

Enhance skills: The course provides practical skills and knowledge that can be applied to various areas and industries.

🔵 Who should take up this ChatGPT Certification Course?

The ChatGPT Certification Course is suitable for a wide range of individuals, including:

AI professionals: This course is ideal for AI professionals who want to gain expertise in ChatGPT and expand their knowledge in the field of AI.

Developers: Developers who want to integrate ChatGPT into their projects and create new AI applications can benefit from the course.

Data scientists: Data scientists who want to understand how ChatGPT can be used to process and analyze large amounts of data can also benefit from the course.

Anyone interested in AI: The course is also suitable for individuals who are interested in AI and want to learn more about the latest developments in the field.

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

Learn prompt engineering techniques to get better results from ChatGPT and other LLMs.

✏️ Course developed by @AniaKubow

⭐️ Contents ⭐️
⌨️ (00:00) Introduction
⌨️ (01:31) What is Prompt Engineering?
⌨️ (02:17) Introduction to AI
⌨️ (03:52) Why is Machine learning useful?
⌨️ (06:36) Linguistics
⌨️ (08:04) Language Models
⌨️ (14:35) Prompt Engineering Mindset
⌨️ (15:38) Using GPT-4
⌨️ (20:41) Best practices
⌨️ (31:20) Zero shot and few shot prompts
⌨️ (35:06) AI hallucinations
⌨️ (36:43) Vectors/text embeddings
⌨️ (40:28) Recap

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama


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इस वीडियो को ज़्यादा लोगों तक पहुंचाने के लिए, इसे https://aloud.area120.google.com के ज़रिए एक आर्टिफ़िशियल वॉइस का इस्तेमाल करके डब किया गया है. सेटिंग्स मेनू में जाकर ऑडियो ट्रैक की भाषा बदली जा सकती है.


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Learn to code for free and get a developer job: https://www.freecodecamp.org

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Learn how to use Pandas and Python for Data Analysis, to Data Cleaning and Data Wrangling. You will learn by creating real life projects interactively to help you take the next step in your Data Science Career.

Learn more about the projects at https://www.datawars.io/freecodecamp

⚠️ Important! We encourage you to try to resolve the projects by yourself first! And watch the solution afterwards ⚠️

💻 Course created by Santiago Basulto from DataWars.
🔗 Find more interactive Data Science projects solve at: https://www.datawars.io

⭐️ Projects Covered ⭐️
⌨️ (0:00:00) Introduction

⌨️ (0:02:22) DataFrames practice: working with English Words [🟢 Easy]
This project focuses on the basics of pandas DataFrames, including understanding its structures and modifying them. The data we're using is a big dictionary of english words.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-english-words

⌨️ (0:33:26) Filtering and sorting with Pokemon data [🟢 Easy]
This project focuses on the main tasks of Data Analysis: filtering and sorting and question/answering. The dataset includes information of pokemons from all generations (to make it more fun!)
🔗 Solve the project by yourself: https://www.datawars.io/fcc-filtering-pokemon

⌨️ (1:24:30) The Birthday Paradox in the NBA [🟡 Intermediate]
The Birthday Paradox answers the question: how many people do you need in the same room in order to have a probability of at least 50% that two people share a birthday. The answer is astonishing! You'll use your findings to find which teams in the NBA share player's birthdays.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-birthday-nba

⌨️ (1:55:28) Matching Strings by Similarity using Levenshtein distance [🟡 Intermediate]
One of the most challenging tasks of Data Cleaning is dealing with Strings. This project is all about string handling and advanced techniques, as using the Combinatorics and the Levenshtein distance to find irregularities in company names.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-string-similarity

⌨️ (2:24:15) Data Cleaning with Google Playstore dataset [🟡 Intermediate]
An all-encompassing project that covers all the aspects of Data Cleaning, including: finding and fixing null values, duplicate values, outliers and more. The data was scraped from the Google Playstore which means that is full of irregularities. The project finishes with some Data Analysis tasks!
🔗 Solve the project by yourself: https://www.datawars.io/fcc-data-cleaning-playstore

⌨️ (3:18:34) Premier League Match Analysis [🔴 Advanced]
This project increases the complexity of your Data Analysis skills, as it combines Data Cleaning, with some analysis based on grouping operations. The dataset comes from the Premier League, the top-division Football/Soccer league in England.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-premier-league

⌨️ (3:53:46) NBA 2017 season analysis: joining and groupby practice [🔴 Advanced]
This project puts your Data Wrangling skills to a test, by asking you to merge different dataframes, clean them, and finish doing some analysis and question/answering. The dataset contains the full information of 2017 NBA statistics.
🔗 Solve the project by yourself: https://www.datawars.io/fcc-nba-analysis


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React: Use the Lifecycle Method componentDidMount


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ChatGPT can now see, hear, and speak! In this new update, ChatGPT gains the ability to interact with the world in a more multimodal way. This means that ChatGPT can now process and understand images and videos, and can also generate speech.

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From the "713: Llama 2, Toolformer and BLOOM: Open-Source LLMs", in which Meta’s AI Research Scientist Thomas Scialom gives us behind-the-scenes insights into developing Llama 2 and what’s in the works for Llama 3. With host @JonKrohnLearns he discusses the future of Artificial General Intelligence, why the Galactica science-focused LLM was taken down, and what he learned from it.

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Shane Legg, the visionary founder of Deepmind has just dropped a bombshell: he envisions DeepMind achieving Artificial General Intelligence, or AGI, by the year 2028. This announcement comes as a seismic shift in the AI landscape, setting the stage for a future where machines possess human-level cognitive abilities. The implications are nothing short of revolutionary, promising to reshape industries, economies, and the very fabric of our existence!
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Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity.
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In this video on Business Analyst Full Course, you will look at topics like the need for having a business analyst, business analyst roles & responsibilities, business analyst skills, business analysis knowledge areas, business analysis with excel, and business analyst vs data analyst. So, let's get started with this business analyst training for beginners!

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Python has recently emerged as one of the fastest-growing programming languages. Not only is it extensively used, but it is also an excellent language to learn if you want to go into programming. On the other hand, Machine Learning trains computers by analysing data and statistics. It represents a step toward artificial intelligence (AI). A machine learning programme analyses data and learns to anticipate outcomes.

There are many reasons why you should consider learning Python for Machine Learning. Out of those, a few important ones are codable simplicity, a huge number of libraries and frameworks, fast development, flexible integration and massive online support.

Many other languages may be used in AI applications, but Python remains the best and should be given critical consideration. It may be used in collaboration with other popular tools in the developer's workflow. Python is now widely used by developers for machine learning applications due to its numerous advantages.

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