🔥 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 𝐰𝐢𝐭𝐡 𝐓𝐞𝐧𝐬𝐨𝐫𝐟𝐥𝐨𝐰 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 : https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka video on 𝐂𝐚𝐧𝐜𝐞𝐫 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐔𝐬𝐢𝐧𝐠 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, will help you understand how to develop models using Convolution Neural Networks. We will also have a discussion on improving model accuracy using pretrained models. Below are the topics covered in Cancer Detection Using Deep Learning video :
00:00:00 Introduction
00:00:52 Introduction to Deep Learning
00:02:57 Deep Learning General Intuition
00:05:43 Image Processing Using DL
00:16:54 Brain Tumor Detection Using Custom Model
01:07:43 Transfer Learning
01:11:21 CNN Architectures

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This Cyber Security full course helps you learn cybersecurity in 12 Hours. In this cybersecurity tutorial for beginners, you will learn the importance of cybersecurity, cybersecurity skills, what cybersecurity means, and the types of cyberattacks with a hands-on demo for each. This video also covers cryptography, ethical hacking, and the top cybersecurity certifications.

Below are the topics covered in this Cyber Security full course video:
Introduction to Cybersecurity
Top Cyber Security Skills
Types of Cyberattacks
What is Cyber Security
Ethical Hacking
Cryptography
CompTIA Security+Cerificatios
CEH Certification
CISSP Certification
Cyber Security Interview Questions and answers

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What Is Cyber Security?
Cyber Security involves techniques that help in securing various digital components, networks, data, and computer systems, from unauthorized digital access. There are several ways to implement cybersecurity, depending on the kind of network you are connected to and the type of cyberattacks you are prone to. A few ways to implement cybersecurity are defining clear boundaries, using network security control devices like Firewalls and IDS, and carrying out security testing.

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Become an industry-ready professional with Advanced Executive Program in Cybersecurity and transform your career in 6 months. This course provides a high-engagement learning experience with real-world applications and is designed for individuals who want to start a new, more fulfilling career. This Advanced Executive Program in Cybersecurity will help you develop expertise in defensive cybersecurity, application security, malware analysis, ethical hacking, and much more. In partnership with IIIT Bangalore and NPCI, this program provides you with a deep understanding needed to spot the opportunities for disruption in the cybersecurity industry.

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What are the eligibility criteria for this Advanced Executive Program in Cybersecurity?
For admission to this Advanced Executive Program in Cybersecurity, candidates:
✅Should have a bachelor's degree in any discipline with an average of 50% or higher marks
✅Prior work experience of 1 year or more
✅May have a non-programming background

Will financial aid be provided for this Advanced Executive Program in Cybersecurity?
To ensure money is not a limiting factor in learning, we offer various financing options to help make this cyber security certification in India financially manageable. For more details, please refer to our ""Admissions Fee and Financing"" section.

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This video on "Copywriting For Beginners 2023" will put a light on market demands for copywriters, companies hiring copywriter with average salaries, and how one can become a skilled copywriter. We will share top 10 copywriting tips, which will help you have a successful copywriting career. So let's begin

00:00 Copywriting for beginners 2023
01:58 What is Copywriting
Top 10 copywriting tips for beginners
02:47 Understanding Target Audience
03:30 Create Strong Headline
04:14 Make Clear and Concise Copy
04:54 Use Active Voice
05:38 Focus on Benefits
06:18 Incorporate Storytelling
06:59 Must Have Call to Actions
07:35 Include Compelling Phrases
08:11 Proofread
08:39 Test Your Copy

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Top 10 Copywriting Tips For Beginners
✅ Understand the target audience: Research your target needs and design your text or copy accordingly. Use language that request your target audience and addresses their specific needs. This will make your copy more relatable and effective in grabbing their attention and ultimately letting them to take action.
✅ Create a strong headline: Headline should not only be attention grabber but also informative showing exact details of what your copy is about in a summarize manner. Tools like headline analyzer from CoSchedule and Monster Insights may help copywriters in this task.
✅ Be clear and concise: Keep your copy simple and straightforward. Avoid using overly technical language or industry jargon that you target audience may not understand. Tools like copy.ai, grammarly and wordtune can help you in this task.
✅ Use active voice: Writing in the active voice makes your copy more engaging and easier to understand. It puts the focus on the subject and highlights their actions, making your copy more relatable. In contrast, writing in the passive voice can make your copy feel distant and disinterested. Scalenut and Sapling are the tools to transform passive voice content into active voice.
✅ Always focus on benefits: When writing your copy, focus on the outcomes and results that your product or service will deliver. This will help to connect with your target audience on an emotional level and convince them to take action.
✅ Watch the complete video to know futher copywriting tips for beginners

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This video, "Who Is A Business Analyst" by Simplilearn, will help you understand who is a business analyst and what does a business analyst do. Here, you will be acquainted with the roles and responsibilities of a business analyst through an interesting story. Business analysts carry out several duties, so let's get started and look at a day in a business analyst's life.
The topics covered in this video on who is a business analyst are:
00:00:00 Who Is A Business Analyst?
00:00:55 Planning the Project
00:01:48 Understand the Business Objectives
00:02:11 Gather Requirements
00:02:34 Allocate Resources
00:03:06 Provide Suggestions
00:03:23 Collect Feedback
00:03:50 Build Reports
00:04:21 Conduct Meetings
00:04:42 Documentation and Presentation
00:05:31 Who Is a Business Analyst

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✅ Business Analysis Certification Overview

This Post Graduate Program in Business Analysis is for professionals looking to pursue a Business Analysis career, understand business analysis techniques, get hands-on experience, and for experienced analysts looking to learn the latest tools and frameworks used by Agile teams.

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ChatGPT is more than just a language model, it can be used to create websites, businesses and much more. And I would know best, as I created, built, and sold a business using OpenAI platform just this year. So in this video, I’m going to explain how to use ChatGPT and its models so you can do the same. The video is structured in three parts.

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This is new and ready for those looking to kickstart their own app or website using the OpenAI GPT models. I've built it on MERN it should save you over 100 hours if you want to build or test your own ideas! This also supports the channel if you have found these videos of benefit!

New - ChatGPT Starter Kit
https://enhanceui.gumroad.com/....l/chatgpt-template-s

Video 1 - What is ChatGPT (Introduction)
https://youtu.be/40Kp_fa8vIw

Video 2 - Crash Course ChatGPT
https://youtu.be/JTxsNm9IdYU

Video 3 - I created a SaaS in 30 days
https://youtu.be/UBG_YiTg_Bs

OpenAI ChatGPT:
https://chat.openai.com/chat

#chatgpt #website #ai

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MIT Introduction to Deep Learning 6.S191: Lecture 7
Deep Learning Limitations and New Frontiers
Lecturer: Ava Amini
2023 Edition

For all lectures, slides, and lab materials: http://introtodeeplearning.com​

Lecture Outline - coming soon!


Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

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

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✅ About ITIL® 4 Foundation Certification Training Course
This ITIL certification introduces learners to ITIL V4 Certification, the newest version of the ITIL 4 exam, to understand and improve an IT-enabled enterprise. This ITIL V4 certification training will help you understand the concepts, languages, best practices, and processes utilized in the ITIL 4 lifecycle.

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- 19 PDUs for self-paced learning
- 22 PDUs for online classroom flexi pass offered
- 30 chapter-end quizzes and 2 industry case studies
- Four simulation exams
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- ITIL central principles
- ITIL process models
- Service level management
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- 15 ITIL best practices

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We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3. We talk about connections to ChatGPT, which has taken the world by storm. We watch GitHub Copilot, itself a GPT, help us write a GPT (meta :D!) . I recommend people watch the earlier makemore videos to get comfortable with the autoregressive language modeling framework and basics of tensors and PyTorch nn, which we take for granted in this video.

Links:
- Google colab for the video: https://colab.research.google.....com/drive/1JMLa53HDu
- GitHub repo for the video: https://github.com/karpathy/ng-video-lecture
- Playlist of the whole Zero to Hero series so far: https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ
- nanoGPT repo: https://github.com/karpathy/nanoGPT
- my website: https://karpathy.ai
- my twitter: https://twitter.com/karpathy
- our Discord channel: https://discord.gg/3zy8kqD9Cp

Supplementary links:
- Attention is All You Need paper: https://arxiv.org/abs/1706.03762
- OpenAI GPT-3 paper: https://arxiv.org/abs/2005.14165
- OpenAI ChatGPT blog post: https://openai.com/blog/chatgpt/
- The GPU I'm training the model on is from Lambda GPU Cloud, I think the best and easiest way to spin up an on-demand GPU instance in the cloud that you can ssh to: https://lambdalabs.com . If you prefer to work in notebooks, I think the easiest path today is Google Colab.

Suggested exercises:
- EX1: The n-dimensional tensor mastery challenge: Combine the `Head` and `MultiHeadAttention` into one class that processes all the heads in parallel, treating the heads as another batch dimension (answer is in nanoGPT).
- EX2: Train the GPT on your own dataset of choice! What other data could be fun to blabber on about? (A fun advanced suggestion if you like: train a GPT to do addition of two numbers, i.e. a+b=c. You may find it helpful to predict the digits of c in reverse order, as the typical addition algorithm (that you're hoping it learns) would proceed right to left too. You may want to modify the data loader to simply serve random problems and skip the generation of train.bin, val.bin. You may want to mask out the loss at the input positions of a+b that just specify the problem using y=-1 in the targets (see CrossEntropyLoss ignore_index). Does your Transformer learn to add? Once you have this, swole doge project: build a calculator clone in GPT, for all of +-*/. Not an easy problem. You may need Chain of Thought traces.)
- EX3: Find a dataset that is very large, so large that you can't see a gap between train and val loss. Pretrain the transformer on this data, then initialize with that model and finetune it on tiny shakespeare with a smaller number of steps and lower learning rate. Can you obtain a lower validation loss by the use of pretraining?
- EX4: Read some transformer papers and implement one additional feature or change that people seem to use. Does it improve the performance of your GPT?

Chapters:
00:00:00 intro: ChatGPT, Transformers, nanoGPT, Shakespeare
baseline language modeling, code setup
00:07:52 reading and exploring the data
00:09:28 tokenization, train/val split
00:14:27 data loader: batches of chunks of data
00:22:11 simplest baseline: bigram language model, loss, generation
00:34:53 training the bigram model
00:38:00 port our code to a script
Building the "self-attention"
00:42:13 version 1: averaging past context with for loops, the weakest form of aggregation
00:47:11 the trick in self-attention: matrix multiply as weighted aggregation
00:51:54 version 2: using matrix multiply
00:54:42 version 3: adding softmax
00:58:26 minor code cleanup
01:00:18 positional encoding
01:02:00 THE CRUX OF THE VIDEO: version 4: self-attention
01:11:38 note 1: attention as communication
01:12:46 note 2: attention has no notion of space, operates over sets
01:13:40 note 3: there is no communication across batch dimension
01:14:14 note 4: encoder blocks vs. decoder blocks
01:15:39 note 5: attention vs. self-attention vs. cross-attention
01:16:56 note 6: "scaled" self-attention. why divide by sqrt(head_size)
Building the Transformer
01:19:11 inserting a single self-attention block to our network
01:21:59 multi-headed self-attention
01:24:25 feedforward layers of transformer block
01:26:48 residual connections
01:32:51 layernorm (and its relationship to our previous batchnorm)
01:37:49 scaling up the model! creating a few variables. adding dropout
Notes on Transformer
01:42:39 encoder vs. decoder vs. both (?) Transformers
01:46:22 super quick walkthrough of nanoGPT, batched multi-headed self-attention
01:48:53 back to ChatGPT, GPT-3, pretraining vs. finetuning, RLHF
01:54:32 conclusions

Corrections:
00:57:00 Oops "tokens from the _future_ cannot communicate", not "past". Sorry! :)
01:20:05 Oops I should be using the head_size for the normalization, not C

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