Let's say you have a model that is working but now you want to be able to save a checkpoint and load it to continue training at a later point. In this video I walkthrough an example of how to do it!

People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx
DL Specialization (affiliate): https://bit.ly/30npNrw
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We present the 1st True 8K drone film by Film Edge, created right here in Kuala Lumpur, Malaysia.

After 2 months of prep, 2 months of shooting, and 6 months of post-processing, we’re finally posting our Airpixel 8K Kuala Lumpur Drone Film.

With worries about the pandemic weighing on our minds, we hope this drone film sends uplifting positive vibes across the nation. We hope it can showcase the beauty of Kuala Lumpur, captured with a high dynamic range and high-resolution camera, and maybe remind us not to lose hope.

Throughout the shoot, we met countless people who shared their knowledge and techniques. We sincerely appreciate these good souls, who volunteered to lend a hand and make our work smoother in completing the film.

Special thanks to Canon Marketing Malaysia — they were the first to believe in us and back us, when we shared our project vision and objectives during our first meeting back in August 2020.

It wasn’t an easy ride throughout the entire process, but we’re so relieved that we managed to overcome all the obstacles in producing this film, with your support.

Hopefully with the kickstart of these Airpixel 8K Kuala Lumpur Drone Films, we are able to inspire many other videomakers to generate 8K films and bring more beauty into this world.

Shot with
DJI Matrice 600 Pro
DJI Matrice 600
Ronin Mx Gimbal
Canon R5, Raw Format (8192 x 4320)
Lens: Canon RF Prime Lenses 35mm, 50mm
Sigma Art Prime Lens 35mm, 50mm, 85mm

BGM: Human-Spirit—Instrumental-Version by Hans-Johnson (artist)

Credit List:
Director : Andy Tan
Executive Producer : Nic Yeow
Producer : Sandra Khor
Drone Pilot : Wayne Ooi
Drone Gimbal Operator : Andy Tan
Drone Tech Supervisor : Adrian Loo
Drone Tech Assistant : Hong Xing Hang
Drone 1st Spotter : Teh Kelven
Production Assistant : Carol Hoo
Production Assistant : James Lam
Production Assistant : James Yap
Editor : Andy Tan
Graphic Designer : Teh Kelven
VFX : Chern Liang
Color Grading : Beh Jing Qiang
ScriptWriter : Zoey Moo
TMO Director : Chris Lee Chee Khoon
TMO Cinematographer : WenChuen Boy
TMO Editor: Teh Kelven, James Yap
Social Media Admin: James Lam

Special Thanks:
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Jin Xi Cheong @ Poladrone
Syahir @ EQ Kuala Lumpur
Cui Yun @ TREC
MonopodCo
Film Troop
Rocket Science Productions
Alex Chu @ March Equipment Store
Andrew @ AKP Studio
Bahrum Jaili
Adam Lokman
Yap Khai Soon
Darryl Chong
L33 Capital Sdn Bhd

Supported by
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Inspired by:
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Deep Nets come in a large variety of structures and sizes, so how do you decide which kind to use? The answer depends on whether you are classifying objects or extracting features. Let’s take a look at your choices.

Deep Learning TV on
Facebook: https://www.facebook.com/DeepLearningTV/
Twitter: https://twitter.com/deeplearningtv

A forewarning: this section contains several new terms, but rest assured – they will all be explained in the upcoming video clips.

If your goal is to train a classifier with a set of labelled data, you should use a Multilayer Perceptron (MLP) or a Deep Belief Network (DBN). Here are some guidelines if you are targeting any of the following applications:

- Natural Language Processing: use a Recursive Neural Tensor Network (RNTN) or Recurrent Net.
- Image Recognition: use a DBN or Convolutional Net
- Object Recognition: use a Convolutional Net or RNTN
- Speech Recognition: use a Recurrent Net

If your goal is to extract potentially useful patterns from a set of unlabelled data, you should use a Restricted Boltzmann Machine (RBM) or some other kind of autoencoder. For any work that involves the processing of time series data, use a Recurrent Net.

What deep nets do you see a use for? Please comment and let me know your thoughts.

Credits:
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Marek Scibior (Prezi creator, Illustrator) -
http://brawuroweprezentacje.pl/
Jagannath Rajagopal (Creator, Producer and Director) -
https://ca.linkedin.com/in/jagannathrajagopal

NVIDIA announced its new CPU today, a collaboration with ARM yielding the "Grace" CPU. The company is also releasing new RTX GPUs (the A4000, A5000, A6000).
Sponsor: Buy Corsair's 5000D Airflow Case on Amazon (https://geni.us/cnVP60)

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NVIDIA's GTC 2021 conference saw the unveil of a series of new GPUs for professionals and data center applications, but all of these were overshadowed by NVIDIA's renewed interest in the CPU space. NVIDIA has been trying to purchase ARM since 2020 (currently pending regulatory approval), and in the meantime, the two organizations are working together to produce the new NVIDIA Grace CPU for data center and server applications. The NVIDIA Grace CPU aims to improve bandwidth of CPU-to-GPU communications and CPU-to-CPU communications, outperforming traditional PCIe signaling with NVIDIA's NVLink.

The GPUs announced are part of the former Quadro line, branding that NVIDIA is slowly moving away from. The A5000 and A4000 GPUs are in the high-end of Ampere RTX cards, with mobile versions also available in Max-Q laptops.

Separately from all of this, NVIDIA talked more about its Omniverse software and a few RTX games, including Black Myth: Wukong, Boundary, Narak: Bladepoint, and Bright Memory. Cyberpunk also got a comically short pseudo-reference.

Like our content? Please consider becoming our Patron to support us: http://www.patreon.com/gamersnexus

TIMESTAMPS

00:00 - NVIDIA GTC 2021 Announcements
01:03 - NVIDIA's New "Grace" ARM CPU
05:11 - New GPUs from NVIDIA: A4000, A5000
10:51 - A10, A16, & Omniverse

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9. Design Hyperledger Fabric Composer Business Network 10.
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In this video on " Build a Game Using Python and ChatGpt", we will learn how to make a tic-tac-toe and snake game using chatgpt. We will be using only the code generated by OpenAI's newest creation, ChatGPT. Below are the topics covered in this game using the chatgpt video:

00:00 Build a Game Using Python and Chatgpt
02:40 What is Chatgpt
04:30 Tic-Tac-Toe game
16:20 Snake Game

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Businesses are integrating large language models (LLM) to build the next generation of applications. Examples include generating personalized marketing text and imagery, summarizing long-form reports, and building entirely new experiences with customer service chatbots. With Azure OpenAI Service, businesses can apply the most advanced AI models—including Dall-E 2, GPT-3.5, GPT-4, Codex, and ChatGPT to address these use-cases, unlock efficiencies, mitigate risk, and more.

To learn more, please check out these resources:
* https://aka.ms/exploreazureopenAI
* https://aka.ms/BuildCollectionBRK214H
* https://aka.ms/learnatbuild


*Speakers:*
* Andy Beatman
* Pablo Castro
* Dom Divakaruni
* Keiji Kanazawa
* Derek Legenzoff
* Christian Montecillo
* Nannette Sperling
* Alison Walters


*Session Information:*
This video is one of many sessions delivered for the Microsoft Build 2023 event. View the full session schedule and learn more about Microsoft Build at https://build.microsoft.com

BRK214H | English (US) | AI


#MSBuild

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.

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If you've been using ChatGPT, you already know the mindblowing potential A.I has! But ChatGPT is only scratching the surface. There is so much more we can do with A.I. to make us more productive and - by the end of the day - generate more revenue.

Let me show you 5 ways to use A.I. to run your online business.

00:00 Introduction
01:31 Idea Generation (ChatGPT)
03:19 Script Writing (GPT-3)
06:12 Creating Content (FeedHive)
08:46 AI Generated Thumbnails (Stable Diffusion)
11:57 Writing Software (ChatGPT + GitHub Copilot)
14:03 What's Next?

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Check out these videos next:

7 AI SaaS Ideas You Can Start In 2023
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5 Smart SaaS Pricing Hacks to Increase MRR
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Welcome to our exhilarating Advanced Python Course For 2023 With Python Projects – a transformative journey into the depths of Python programming! In this power-packed series, we'll equip you with the tools and knowledge to take your Python skills from competent to extraordinary. Whether you're an aspiring developer or a seasoned coder, this course is designed to elevate your coding prowess and explore Python's most advanced concepts. Get ready to unravel the magic of object-oriented programming (OOP), conquer Python's powerful libraries, and dive into the world of functional programming. We'll navigate through classes, objects, inheritance, iterators, and generators, unlocking Python's true potential. From mastering file handling and exception handling to embracing automation through lambda functions, we've got you covered! Plus, we'll introduce you to the top Python libraries of 2023 and delve into the might of NumPy and Pandas for data science.

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00:00:00 Introduction to Python

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This AI and Machine Learning Bootcamp in collaboration with Caltech, will help you advance your career as an AI and ML specialist. The AI and ML Bootcamp includes live classes delivered by industry experts, hands-on labs, Industry-relevant projects, and masterclasses by Caltech professors.

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Learn the basics of reinforcement learning and how to implement it using Gymnasium (previously called OpenAI Gym). Gymnasium is an open source Python library maintained by the Farama Foundation that provides a collection of pre-built environments for reinforcement learning agents. It provides a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API.

Reinforcement learning is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward.

💻 Google Colab Notebook (full tutorial code): https://colab.research.google.....com/drive/1oNxRpRnht

Gymnasium documentation: https://gymnasium.farama.org/

✏️ Course developed by @EverythingTechWithMustafa
🔗 Mustaf on LinkedIn: https://www.linkedin.com/in/mu....stafa-esoofally-aab0

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:04:19) Reinforcement Learning Basics (Agent and Environment)
⌨️ (0:12:15) Introduction to Gymnasium
⌨️ (0:14:59) Blackjack Rules and Implementation in Gymnasium
⌨️ (0:18:27) Solving Blackjack
⌨️ (0:19:46) Install and Import Libraries
⌨️ (0:23:19) Observing the Environment
⌨️ (0:27:55) Executing an Action in the Environment
⌨️ (0:33:01) Understand and Implement Epsilon-greedy Strategy to Solve Blackjack
⌨️ (0:42:28) Understand the Q-values
⌨️ (0:47:29) Training the Agent to Play Blackjack
⌨️ (0:57:10) Visualize the Training of Agent Playing Blackjack
⌨️ (1:04:34) Summary of Solving Blackjack
⌨️ (1:09:57) Solving Cartpole Using Deep-Q-Networks(DQN)
⌨️ (2:29:29) Summary of Solving Cartpole
⌨️ (2:34:07) Advanced Topics and Introduction to Multi-Agent Reinforcement Learning using Pettingzoo

Correction:
00:09 Gymnasium is maintained by the Farama Foundation and is not associated with OpenAI.

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Referencias del video:
Tyson, J. (2001). Cómo funciona la visión nocturna. How Stuff Works. - https://ve42.co/HSWNightVision
Montoro, H. P. Intensificación de imágenes: la tecnología de la visión nocturna. Photonics. - https://ve42.co/PhotonicsTech
Brain Stuff - HowStuffWorks a través de YouTube - https://ve42.co/HSWVideo
Photonis a través de YouTube - https://ve42.co/Photonis
Operator Drewski a través de YouTube - https://ve42.co/NVGaming
Dispositivo de visión nocturna a través de Wikipedia - https://ve42.co/NVWiki
Intensificador de imagen a través de Wikipedia - https://ve42.co/Intensifier
Lodriguss, J. Cómo funcionan las cámaras digitales. AstroPix. - https://ve42.co/AstroPix
Kinka-Byo. (2019). ¿Cuál es la causa física del aumento de ruido a ISO alto? StackExchange. - https://ve42.co/PhotoISO
Macias, A. (2015). Las NVG secretas que usó el SEAL Team Six en la incursión contra Bin Laden. Business Insider. - https://ve42.co/BINightVision
Van Dommelen, L. Emisión termoiónica. Mecánica cuántica para ingenieros. - https://ve42.co/Thermoionic
Nave, R. (2016). Radiación de cuerpo negro. HyperPhysics. - https://ve42.co/BlackBody
Terminología de visión nocturna - Generaciones. ModArmory. - https://ve42.co/ModArmory
NASA (2018). Detectores de rayos X - Detección de corriente eléctrica. - https://ve42.co/NASAXRay

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Metraje de Splinter Cell, a través de Ubisoft en YouTube - https://ve42.co/SplinterCell
Escena de visión nocturna de Step Brothers, a través de masusockvevo en YouTube - https://ve42.co/StepBrothers
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Metraje de la cámara de imagen térmica FLIR K2, a través de Teledyne FLIR en YouTube - https://ve42.co/FLIRK2
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Dirigido por Emily Zhang
Escrito por Emily Zhang y Derek Muller
Editado por Trenton Oliver
Animado por Mike Radjabov, Fabio Albertelli e Ivy Tello
Filmado por Trenton Oliver, Emily Zhang, Derek Muller y Raquel Nuno
Producido por Emily Zhang y Derek Muller

Miniatura por Ren Hurley
Video/fotos adicionales proporcionados por Getty Images y Pond5
Música de Epidemic Sound

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La gente ha sido testigo de las supernovas desde hace milenios, pero ¿qué tipo de amenaza posan para el planeta Tierra? Este video es patrocinado por Brilliant. Puedes comenzar gratis, o las primeras 200 personas en suscribirse vía https://brilliant.org/veritasium obtendrán un 20% de descuento.

Agradecemos enormemente al Prof. Hans-Thomas Janka por ayudarnos con la física de una supernova y GRBs. También al Prof. Brian Thomas por toda su ayuda con los efectos terrestres de las supernovas y GRBs. Este video no hubiera sido posible sin ninguno de ellos. Además al Dr. Luke Barnes por su ayuda inicial en la investigación de la literatura relacionada.

El dato sobre la bomba de hidrogeno vs la supernova fue sacado de este gran artículo por xkcd/Randall Munroe - https://what-if.xkcd.com/73/ (based on the calculation by Andrew Karam, 2002)

El video de la burbúja cósmica de: https://www.cfa.harvard.edu/ne....ws/1000-light-year-w

Referencias: Melott, A. et al. (2019). Hypothesis: Muon radiation dose and marine megafaunal extinction at the End-Pliocene supernova. Astrobiology, 19(6), 825-830. – https://ve42.co/Melott1

Thomas, B. C. et al. (2016). Terrestrial effects of nearby supernovae in the early Pleistocene. The Astrophysical Journal Letters, 826(1), L3 – https://ve42.co/Thomas1

Melott, A. L., & Thomas, B. C. (2019). From cosmic explosions to terrestrial fires?. The Journal of Geology, 127(4), 475-481. – https://ve42.co/Melott2

Fields, B. et al. (2019). Near-Earth supernova explosions: Evidence, implications, and opportunities. arXiv preprint arXiv:1903.04589. – https://ve42.co/Fields1

Thomas, B. C., Atri, D., & Melott, A. L. (2021). Gamma-ray bursts: not so much deadlier than we thought. Monthly Notices of the Royal Astronomical Society, 500(2), 1970-1973. – https://ve42.co/Thomas2

Melott, A. et al. (2004). Did a gamma-ray burst initiate the late Ordovician mass extinction?. International Journal of Astrobiology, 3(1), 55-61. – https://ve42.co/Melott3

Firestone, R. B. (2014). Observation of 23 supernovae that exploded less than 300 pc from Earth during the past 300 kyr. The Astrophysical Journal, 789(1), 29. – https://ve42.co/firestone1

Janka, H. T. (2017). Neutrino emission from supernovae. arXiv preprint arXiv:1702.08713. – https://ve42.co/Janka1

Janka, H. T., & Hillebrandt, W. (1989). Neutrino emission from type II supernovae-an analysis of the spectra. Astronomy and astrophysics, 224, 49-56. – https://ve42.co/Janka2

Janka, H. T. (2017). Neutrino-driven explosions. arXiv preprint arXiv:1702.08825. – https://ve42.co/Janka3

Karam, P. A. (2002). Gamma and neutrino radiation dose from gamma ray bursts and nearby supernovae. Health physics, 82(4), 491-499. – https://ve42.co/Karam1

Melott, A. L., Thomas, et al.. (2017). A supernova at 50 pc: effects on the Earth's atmosphere and biota. The Astrophysical Journal, 840(2), 105. – https://ve42.co/Melott4

Ludwig, P., et al. (2016). Time-resolved 2-million-year-old supernova activity discovered in Earth’s microfossil record. Proceedings of the National Academy of Sciences, 113(33), 9232-9237. – https://ve42.co/Ludwig1

Gritschneder, et al. (2011). The supernova triggered formation and enrichment of our solar system. The Astrophysical Journal, 745(1), 22. – https://ve42.co/Gritschneder1

Motizuki, Y., Takahashi, et al. (2009). An Antarctic ice core recording both supernovae and solar cycles. arXiv preprint arXiv:0902.3446. – https://ve42.co/Motizuki

Zucker, C. et al. (2022). Star formation near the Sun is driven by expansion of the Local Bubble. Nature, 601(7893), 334-337. – https://ve42.co/Zucker1

Hirata, K. et al.(1987). Observation of a neutrino burst from the supernova SN1987A. – https://ve42.co/Hirata1

Hayes, L. A., & Gallagher, P. T. (2022). A Significant Sudden Ionospheric Disturbance Associated with Gamma-Ray Burst GRB 221009A. Research Notes of the AAS, 6(10), 222.

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Escrito por Petr Lebedev & Derek Muller
Editado por Fabio Albertelli
Animado por Fabio Albertelli, Jakub Misiek, Alex Drakoulis, Ivy Tello, Mike Radjabov, and Charlie Davies
Filmado por Derek Muller
Investigación adicional por Kovi Rose & Katie Barnshaw
Videos/fotos provistos por NASA, ESA, Pond5, and Getty Images
Producido por Derek Muller, Petr Lebedev, and Emily Zhang