How to Create a Text Message in Adobe Premiere Pro CC (2023)

By AdobeMasters
Published: Aug 07, 2023

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Check out my Premiere Pro Course: https://www.udemy.com/course/premiere-pro-course/?referralCode=AF659E18BEF06A7F4955

Get near unlimited stock footage and premiere pro templates: http://1.envato.market/c/1413971/298927/4662

Join the Community at: https://adobemasters.net/
Request a Tutorial at: https://adobemasters.net/request-a-tutorial/

If you want to learn more about the Adobe products. Here are a couple of cheap courses I learned from.
http://adobemasters.net/courses/

Subscribe to see more Adobe related content, videos every other day.

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Make A VIRAL Hyperlapse In PREMIERE PRO

By Olufemii
Published: Aug 04, 2023

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🔥 Limited Time Get The Paper Assets Pack for $19.99 (Save $30): https://bit.ly/3INZWPZ

Join Quinn as she takes you on a whirlwind tour of her video masterpiece for Renaissance Hotels! Learn how to create a hyperlapse using Premiere Pro. Dive into keyframing, speed ramps, and mask transitions. With cameras like the Insta360 1rs one inch and Sony A7 III, Quinn crafts stunning visuals, showcasing different parts of the hotel. From balancing on a monopod to weaving edits in Premiere, she unfolds her techniques with flair and fun.

Find Quinn on Instagram here: https://www.instagram.com/quinn_films/
Smooth Hyperlapse Trick Tutorial: https://youtu.be/kLBzhnxn6Uk

#hyperlapse #insta360 #sonya7iii

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TensorFlow Course – Building and Evaluating Medical AI Models

By freeCodeCamp.org
Published: Aug 03, 2023

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Learn how to build and evaluate medical AI models with TensorFlow. This is a great, real world project for improving your machine learning skills. You will use TensorFlow to evaluate chest x-rays.

✏️ Dr. Jason Adleberg teaches this course.
Jason on Twitter: https://www.twitter.com/pixels2patients
Jason on Linkedin: https://www.linkedin.com/in/jason-adleberg-6b444b52

💻 Colab Notebook: https://colab.research.google.com/drive/1klBxr93NYXrLFOVMXhm0RbVm5PIjfXQn

⭐️ Course Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:01:11) Getting started with Google Colab
⌨️ (0:01:50) Facts about Chest X-Rays
⌨️ (0:06:36) 1. Defining a Problem
⌨️ (0:12:33) 2. Preparing the Data
⌨️ (0:19:45) 3. Training the Model
⌨️ (0:32:00) 4. Running the Model
⌨️ (0:37:05) 5a. Evaluating Performance
⌨️ (0:48:44) 5b. Stats: Histogram, Sensitivity & Specificity
⌨️ (1:01:00) 5c. Stats: AUC Curve
⌨️ (1:08:19) 6. Saving our Model

🎉 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

—

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

Read hundreds of articles on programming: https://freecodecamp.org/news

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Machine Learning Safety – Full Course from the Center for AI Safety

By freeCodeCamp.org
Published: Aug 02, 2023

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ML systems are rapidly increasing in size, are acquiring new capabilities, and are increasingly deployed in high-stakes settings. As with other powerful technologies, safety for ML should be a leading research priority. In this course we’ll discuss how researchers can shape the process that will lead to strong AI systems and steer that process in a safer direction. We’ll cover various technical topics to reduce existential risks (X-Risks) from strong AI, namely withstanding hazards (“Robustness”), identifying hazards (“Monitoring”), reducing inherent ML system hazards (“Alignment”), and reducing systemic hazards (“Systemic Safety”). At the end, we will zoom out and discuss additional abstract existential hazards and discuss how to increase safety without unintended side effects.

✏️ See course.mlsafety.org for more.

⭐️ Contents ⭐️
(0:00:00) Introduction
(0:11:09) Deep Learning Review
(0:52:41) Risk Decomposition
(1:06:57) Accident Models
(1:39:22) Black Swans
(1:58:45) Adversarial Robustness
(2:29:40) Black Swan Robustness
(2:52:56) Anomaly Detection
(3:35:32) Interpretable Uncertainty
(3:59:09) Transparency
(4:12:22) Trojans
(4:22:52) Detecting Emergent Behavior
(4:43:07) Honest Models
(5:00:06) Machine Ethics
(5:52:08) ML for Improved Decision-Making
(6:04:40) ML for Cyberdefense
(6:25:00) Cooperative AI
(6:58:33) X-Risk Overview
(7:05:23) Possible Existential Hazards
(7:13:16) AI and Evolution
(8:03:08) Safety-Capabilities Balance
(8:21:07) Review and Conclusion

🎉 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

—

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

Read hundreds of articles on programming: https://freecodecamp.org/news

[READ MORE]

”