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In this video we look at the datasets that are available to us through TensorFlow Datasets (tfds) and how we load them and then doing preprocessing, shuffling, batching, prefetching etc. For the example we load an image dataset (mnist) and a text dataset (imdb) and create simple models to do image classification and sentiment analysis.
New packages/imports we used in the video:
https://anaconda.org/conda-forge/matplotlib (pip install matplotlib)
https://anaconda.org/anaconda/tensorflow-datasets (pip install tensorflow_datasets)
I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
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OUTLINE:
0:00 - Introduction
0:16 - Keras vs TFDS vs tf.data
1:54 - Imports
2:38 - Image Loading with TFDS
12:59 - Text loading with TFDS
28:15 - Results and Ending
Artist Refik Anadol doesn't work with paintbrushes or clay. Instead, he uses large collections of data and machine learning algorithms to create mesmerizing and dynamic installations.
Machine Hallucination at Artechouse NYC: https://www.artechouse.com/nyc
WDCH Dreams: https://www.laphil.com/visit/w....hen-youre-here/wdchd
Winds of Boston: http://refikanadol.com/works/w....ind-of-boston-data-p
Melting Memories: http://refikanadol.com/works/melting-memories/
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How This Guy Uses A.I. to Create Art | Obsessed | WIRED
🔥 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐏𝐀 𝐮𝐬𝐢𝐧𝐠 𝐔𝐢𝐏𝐚𝐭𝐡 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠:https://www.edureka.co/robotic....-process-automation- (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka session on "Who is a RPA Developer?" will provide a glimpse of the "RPA Developer" and what RPA Developer Roadmap.
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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐒𝐞𝐥𝐞𝐧𝐢𝐮𝐦 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 : https://www.edureka.co/seleniu....m-certification-trai (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka Python Selenium tutorial will help you in learning how to perform functional testing using Python.
00:00:00 Introduction
00:01:35 What is Functional testing?
00:04:34 What is Selenium
00:10:33 Selenium and Python binding
00:17:29 Getting Started - Python Selenium
00:54:30 Locating Elements
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In this Selenium tutorial for beginners video, we will learn about Selenium and have a hands-on demo on the working of Selenium IDE and Selenium WebDriver. Selenium is an automated testing tool that tests web applications across various platforms and browsers. Selenium IDE, Selenium RC, Selenium WebDriver, and Selenium Grid constitute the Selenium suite.
The following are the topics included in this Selenium Tutorial video:
0:00 Selenium Tutorial for Beginners Introduction
1:04 Manual testing and its limitations
08:43 Selenium suite of tools
11:42 Selenium IDE with demo
27:30 Selenium RC
33:35 Selenium WebDriver with demo
57:59 Selenium Grid
1:02:32 Advantages of Selenium testing
1:04:17 Limitations of Selenium testing
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What is Selenium?
Selenium is an automated testing tool that tests web applications across various platforms and browsers. WebDriver happens to be one of the Selenium tools with a simple yet robust architecture. It controls the browser based on the user program. WebDriver revolutionized automation testing and continues to do so.
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Ilya Sutskever, one of the leading AI scientists behind ChatGPT, reflects on his founding vision and values. In conversations with the film-maker Tonje Hessen Schei as he was developing the chat language model between 2016 and 2019, he describes his personal philosophy and makes startling predictions for a technology already shaping our world. Reflecting on his ideas today, amid a global debate over safety and regulation, we consider the opportunities as well as the consequences of AI technology. Ilya discusses his ultimate goal of artificial general intelligence (AGI), ‘a computer system that can do any job or task that a human does, but better’, and questions whether the AGI arms race will be good or bad for humanity.
These filmed interviews with Ilya Sutskever are part of a feature-length documentary on artificial intelligence, called iHuman
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#IlyaSutskever #ChatGPT #ArtificialIntelligence #AGI #OpenAI #Documentary
1 Sugar Shack - - The Fireballs
2 Surfin' U.S.A. - The Beach Boys
3 The End of the World - Skeeter Davis
4 Rhythm of the Rain - The Cascades
5 He's So Fine - The Chiffons
6 Blue Velvet - Bobby Vinton
7 Hey Paula - Paul & Paula
8 Fingertips - Little Stevie Wonder
9 Washington Square - The Village Stompers
10 It's All Right - The Impressions
11 Can't Get Used to Losing You - Andy Williams
12 My Boyfriend's Back - The Angels
13 Sukiyaki - Kyu Sakamoto
14 She's a Fool - Lesley Gore
15 So Much in Love - The Tymes
16 Puff, the Magic Dragon - Peter, Paul and Mary
17 Blowin' in the Wind - Peter, Paul and Mary
18 I'm Leaving It Up to You - Dale and Grace
19 Deep Purple - Nino Tempo & April Stevens
20 Wipe Out - The Surfaris
21 I Love You Because - Al Martino
22 Wild Weekend - The Rebels
23 You're the Reason I'm Living - Bobby Darin
24 Walk Like a Man - The Four Seasons
25 Mockingbird - Inez and Charlie Foxx
26 I Will Follow Him - Little Peggy March
27 Pipeline - The Chantays
28 Surf City - Jan and Dean
29 It's My Party - Lesley Gore
30 Blame It on the Bossa Nova - Eydie Gorme
Ready to become a certified watsonx Generative AI Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdnZTF
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Can a drone deliver packages safely and efficiently? 🤖 Martin Keen breaks down the 5 types of AI agents—from reflex to learning models—and their role in robotics, decision-making, and automation. Learn how goal-driven and utility-based AI adapt to workflows and complex environments.
Intro - 0:00
Simple Reflex Agent - 0:50
Model-Based Reflex Agent - 2:49
Goal-Based AI Agent - 4:20
Utility Based AI Agent- 5:43
Learning AI Agent - 6:55
Use Cases - 8:22
AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdnZTX
#aiagents #machinelearning #ai
Course details: https://stanford.io/4qjWTCk
Think back to the first time you had to tell a direct report their work wasn’t good enough, or persuade your supervisor to change course. For most new managers, those difficult conversations might not have gone as planned. But research shows these early moments can shape the trajectory of your entire career. The good news is you don’t have to wait for the next high-stakes conversation to get it right.
In this course, Stanford faculty combine decades of research with the emergent superpowers of generative AI to give you a “practice field” for leadership. You will rehearse critical conversations in a low-stakes environment and gain the skills and confidence to lead with authority and empathy.
You will learn to:
- Craft clear, respectful communication strategies that shift outcomes
- Give and receive constructive feedback that accelerates growth
Using generative AI, you will role-play high-pressure situations such as confronting difficult team members, motivating diverse talent, or disagreeing with your manager. Each practice round gives you structured, real-time feedback on tone, presence, and empathy so you can iterate and improve.
The course begins with three preset scenarios drawn from the experiences of Stanford alumni.
For each, you will:
- Observe: Hear how young leaders confronted real challenges
- Practice: Role-play with an AI partner as your conversational counterpart
- Get Feedback: Receive personalized feedback from our tough conversation AI coach
-Reflect and Repeat: Apply insights, refine your approach, and try again
Finally, you will design your own AI conversation partner for a current workplace challenge, building a personalized tool you can use beyond the course. Along the way, Stanford faculty share research, alumni share lived experiences, and you gain the playbook to shift your career trajectory.
Please note: This course requires a free ChatGPT account to participate in practice activities.
What makes a system-support machine learning model development? Find out how to transit yourself into the machine learning engineering domain, with Chi Wang, the co-author of the book 📖 Engineering Deep Learning Systems 📖
This video is an excerpt from "What Developers Need to Know to Design Machine Learning Systems" - a live-streaming session by Chi Wang. To watch the full video, visit http://mng.bz/BZr8.
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Engineering Deep Learning Systems | http://mng.bz/lR58
To save 40% off this book use discount code: watchchiwang40
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About the book:
"Engineering Deep Learning Systems" teaches you to design and implement an automated platform to support creating, training, and maintaining deep learning models. In it, you’ll learn just enough about deep learning to understand the needs of the data scientists who will be using your system. You’ll learn to gather requirements, translate them into system component design choices, and integrate those components into a cohesive whole. A complete example system and insightful exercises help you build an intuitive understanding of DL system design.
