In this video we go through how to implement a dynamic algorithm for solving the sequence alignment or edit distance problem. This is also referred to as the Needleman Wunsch algorithm, it seems as if this algorithm has quite many names :)

Code repository:

https://github.com/AladdinPerz....on/Algorithms-Collec

I recommend watching the explanation video before watching this implementation:

https://youtu.be/bQ7kRW6zo9Y

While the Transformer architecture is used in a variety of applications across a number of domains, it first found success in natural language. Today, Transformers remain the de facto model in language - they achieve state-of-the-art results on most natural language benchmarks, and can generate text coherent enough to deceive human readers. In this talk, we will review recent progress in neural language modeling, discuss the link between generating text and solving downstream tasks, and explore how this led to the development of GPT models at OpenAI. Next, we’ll see how the same approach can be used to produce generative models and strong representations in other domains like images, text-to-image, and code. Finally, we will dive into the recently released code generating model, Codex, and examine this particularly interesting domain of study.


Mark Chen is a research scientist at OpenAI, where he manages the Algorithms Team. His research interests include generative modeling and representation learning, especially in the image and multimodal domains. Prior to OpenAI, Mark worked in high frequency trading and graduated from MIT. Mark is also a coach for the USA Computing Olympiad team.


A full list of guest lectures can be found here: https://www.youtube.com/playli....st?list=PLoROMvodv4r

0:00 Introduction
0:08 3-Gram Model (Shannon 1951)
0:27 Recurrent Neural Nets (Sutskever et al 2011)
1:12 Big LSTM (Jozefowicz et al 2016)
1:52 Transformer (Llu and Saleh et al 2018)
2:33 GPT-2: Big Transformer (Radford et al 2019)
3:38 GPT-3: Very Big Transformer (Brown et al 2019)
5:12 GPT-3: Can Humans Detect Generated News Articles?
9:09 Why Unsupervised Learning?
10:38 Is there a Big Trove of Unlabeled Data?
11:11 Why Use Autoregressive Generative Models for Unsupervised Learnin
13:00 Unsupervised Sentiment Neuron (Radford et al 2017)
14:11 Radford et al 2018)
15:21 Zero-Shot Reading Comprehension
16:44 GPT-2: Zero-Shot Translation
18:15 Language Model Metalearning
19:23 GPT-3: Few Shot Arithmetic
20:14 GPT-3: Few Shot Word Unscrambling
20:36 GPT-3: General Few Shot Learning
23:42 IGPT (Chen et al 2020): Can we apply GPT to images?
25:31 IGPT: Completions
26:24 IGPT: Feature Learning
32:20 Isn't Code Just Another Modality?
33:33 The HumanEval Dataset
36:00 The Pass @ K Metric
36:59 Codex: Training Details
38:03 An Easy Human Eval Problem (pass@1 -0.9)
38:36 A Medium HumanEval Problem (pass@1 -0.17)
39:00 A Hard HumanEval Problem (pass@1 -0.005)
41:26 Calibrating Sampling Temperature for Pass@k
42:19 The Unreasonable Effectiveness of Sampling
43:17 Can We Approximate Sampling Against an Oracle?
45:52 Main Figure
46:53 Limitations
47:38 Conclusion
48:19 Acknowledgements

#gpt3

🔥NIT Warangal Post Graduate Diploma in AI & Machine Learning with Edureka: https://www.edureka.co/nitw-ai-ml-pgp
This Edureka video of "Chatbots using TensorFlow" gives you an idea about what are chatbots and how did they come into existence. It provides a brief introduction about all the layers involved in creating a chatbot using TensorFlow and Machine Learning.

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How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
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3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course

Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.


- - - - - - - - - - - - - -

Who should go for this course?

The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'

2. Analytics Managers who are leading a team of analysts

3. Business Analysts who want to understand Deep Learning (ML) Techniques

4. Information Architects who want to gain expertise in Predictive Analytics

5. Professionals who want to captivate and analyze Big Data

6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

- - - - - - - - - - - - - -

Why Learn Deep Learning With TensorFlow?

TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world.

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⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

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Learn how to use the OpenAI API to create five projects, including a ChatGPT clone, a DALL-E Image Creator, and a SQL Generator. This is a dive deep into the world of the OpenAI API, exploring its diverse capabilities and potential applications.

✏️ Course created by @AniaKubow

Donate to freeCodeCamp: https://www.freecodecamp.org/donate/

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:02:57) Authentication
⌨️ (0:06:22) Models
⌨️ (0:07:27) Text Completions
⌨️ (0:18:31) Creating effective prompts
⌨️ (0:20:18) Chat Completions
⌨️ (0:30:14) Chat Completion Project 1 | JavaScript
⌨️ (1:15:41) Chat Completion Project 2 | React + Node.js
⌨️ (2:20:59) DALL-E Model
⌨️ (2:21:41) Image Generation
⌨️ (2:27:04) Image Variation
⌨️ (2:27:44) Image Edits
⌨️ (2:28:28) Image Generation Project 1 | JavaScript
⌨️ (3:00:29) Image Generation Project 2 | React + Node.js + openai npm library
⌨️ (4:23:39) SQL Generator Project | TypeScript + Node.js + openai npm library
⌨️ (5:17:00) The End

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شوف الكنز الجديد ده..
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00:04:47 What is SQL ?
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04:45:53 Where vs Having by Clauses Explained

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Во время холодной войны один американский инженер придумал космическое оружие – вольфрамовые стержни, размером с телефонный столб. Дерек с канала Veritasium собрал команду специалистов и проверил эффективность подобного снаряда на практике.

Перевод: Алексей Лоскутов
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© https://www.youtube.com/c/veritasium/
Источник: https://youtu.be/J_n1FZaKzF8

( Data Science Training - https://www.edureka.co/data-sc....ience-r-programming- )
This Logistic Regression Tutorial shall give you a clear understanding as to how a Logistic Regression machine learning algorithm works in R. Towards the end, in our demo, we will be predicting which patients have diabetes using Logistic Regression!

In this Logistic Regression Tutorial video you will understand:

1) The 5 Questions asked in Data Science
2) What is Regression?
3) Logistic Regression - What and Why?
4) How does Logistic Regression Work?
5) Demo in R: Diabetes Use Case
6) Logistic Regression: Use Cases

Subscribe to our channel to get video updates. Hit the subscribe button above.
Check our complete Data Science playlist here: https://goo.gl/60NJJS

#LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience

How it Works?

1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

- - - - - - - - - - - - - -

Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

- - - - - - - - - - - - - -

Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

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

Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
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LinkedIn: https://www.linkedin.com/company/edureka

Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "

‘Artificial Paradise' featuring “I Ain’t Worried” available now: https://onerepublic.lnk.to/ArtificialParadise 

Stream OneRepublic’s “I Ain’t Worried” from ‘Top Gun: Maverick’:
http://OneRepublic.lnk.to/iaintworried

Listen to “Top Gun: Maverick (Music From The Motion Picture)”, soundtrack out now:
http://TopGunMaverick.lnk.to/Soundtrack

Listen to OneRepublic:
Spotify: http://smarturl.it/1RSpotify
Apple Music: https://apple.co/3B4u43p

Shop OneRepublic: http://smarturl.it/1RShop
Sign up for email updates: http://smarturl.it/1REmail
Catch OneRepublic on tour: https://www.onerepublic.com/tour

Follow OneRepublic:
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Follow Top Gun:
https://www.instagram.com/topgunmovie/
https://twitter.com/topgunmovie
https://www.facebook.com/TopGunMovie/
Website: https://www.topgunmovie.com/

“I Ain’t Worried” Lyrics:
i don’t know what you’ve been told
but time is running out no need to take it slow
im stepping to you toe to toe
i should be scared honey maybe so

but i aint worried bout it right now (right now)
keeping dreams alive, 1999, heroes
i aint worried bout it right now (right now)
swimmin in the floods, dancing on the clouds, below

i aint worried bout it
i aint worried bout it

I don’t know what you’ve been told
but time is running out so spend it like its gold
im living like I’m 9 zeros
got no regrets even when I’m broke
yeah
im at my best when i got something
im wanting to steal
way too busy for them problems
and problems to feel (yeah yeah)
no stressing just obsessin with sealin the deal
ill take it in and let it go

but i aint worried bout it right now (right now)
keeping dreams alive, 1999, heroes
i aint worried bout it right now (right now)
swimmin in the floods, dancing on the clouds, below

i aint worried bout it
i aint worried bout it

oooooooooo
i aint worried
oooooooo
oh no no

i aint worried bout it right now (right now)
keeping dreams alive, 1999, heroes
i aint worried bout it right now (right now)
swimmin in the floods, dancing on the clouds, below
i aint worried bout it
i aint worried bout it
i aint worried bout it

#OneRepublic #IAintWorried #TopGunMaverick

Music video by OneRepublic performing I Ain't Worried. © 2022 Mosley Music/Interscope Records

http://vevo.ly/0zOiFO

Credits :
Lofi (Slowed + Reverb) By - BARATO NATION
Present By - BARATO NATION


Song Credits :
Song: Sifar Safar
Singer/Lyrics/Composer: Karan Aujla
Music: Mxrci
Video Director: Qarn Mallhi

Official audio for I Want To Wake Up by Pet Shop Boys taken from their 1987 album, 'Actually'.

Subscribe for more here: http://smarturl.it/petshopboysyoutube

Follow Pet Shop Boys:
Website: https://www.petshopboys.co.uk
Instagram: https://petshopboys.lnk.to/instagramID
Facebook: https://petshopboys.lnk.to/facebookID
Twitter: https://petshopboys.lnk.to/twitterID
Spotify: https://petshopboys.lnk.to/spotifyID
Apple Music - https://petshopboys.lnk.to/applemusicID

Lyrics:

[Chorus]
Hit music on the radio
Hit music on the radio

[Verse 1]
When you dance with me we dance forever
All night long to your favourite

[Chorus]
Hit music on the radio
Hit music on the radio

[Verse 2]
When you dance with me we dance forever
All night long to the latest song
Live a lie, dance together
All night long to your favourite

[Chorus]
Hit music
Hit music

[Bridge]
I've been working hard all day
To pay the bills I have to pay
Don't have the strength to work all night
Or fight until it's almost light

[Chorus]
Music on the radio
D-dance music at the disco

[Verse 3]
Live a lie, dance together
All night long to your favourite song
Live and die, it's all that we know
I need a friend at the journey's end

[Chorus]
Hit music in stereo

[Interlude]

[Verse 4]
It's all about love and it's about forgetting
Choose a song when the night's too long
We all need love and we want protection
I need a friend at the journey's end
In Kensington or Spanish Harlem
All night long to your desperate

[Chorus]
Hit music on the radio
Music at the disco

[Chorus]
Hit music on the radio
Hit music on the radio

#PetShopBoys #HitMusic