I remember watching this on TV when I was a kid and it blew my mind.

It is hands-down the best explanation of four dimensions, curved space, and more – all done in Carl Sagan’s trademark awesomeness.

It may not come up in everyday dinner conversations, but non-Euclidean distances can have some interesting real world applications.

Zach Star explains why.

Geek’s Lesson provides this full nine hour source on quantum mechanics.

Quantum mechanics (QM; also known as #quantum #physics, quantum theory, the wave mechanical model, or #matrixmechanics), including quantum field theory, is a fundamental theory in physics which describes nature at the smallest scales of energy levels of atoms and subatomic particles.

• (0:00) Lesson 1: Fundamentals
• (10:03) Lesson 2: Complex Numbers in Quantum Mechanics
• (27:20) Lesson 3: Representing Complex Things
• (43:03) Lesson4: Superposition and Stationary States
• (1:0:00) Lesson5: Infinite Square Well
• (1:19:48) Lesson 6: More ISW + Dirac Notation
• (1:39:07) Lesson 9: QSHO, Operator Method, part 1
• (1:55:37) Lesson 10: QSHO Part 2
• (2:18:42) Lesson11 SHO Analytical
• (2:32:56) Lesson13 Free Particle (redo)
• (3:00:28) Lesson14 More Fourier Transforms, inner products
• (3:22:10) Lesson15 Delta Bound States
• (3:32:50) Lesson16: Scattering States of the Dirac Delta Potential + More DFT concepts
• (4:06:17) Finite Square Well (updated)
• (4:32:43) Tunneling and Bonding
• (5:08:05) Review (or intro) to Linear Algebra + Notation
• (6:03:52) Formalism I
• (6:14:20) Formalism II More Quantum Formalism
• (6:43:49) Formalism III: Time Evolution + More Change of Basis
• (7:39:45) Exam 3 Prep, More time evolution of Ammonia molecule
• (7:55:25) SWE in 3D
• (8:25:07) Hydrogen Solutions + Angular Momentum
• (8:31:14) Angular Momentum-II
• (8:57:34) Spin 1/2

Jon Levesque Tech shows us Microsoft Lists and Power Automate & how to use a list to power your flow to build an automated set of follow up emails.

Content index:

• 00:00 – Introduction
• 03:03 – Looking at the scenario
• 03:56 – Take a look at Microsoft Lists
• 04:30 – New List Menu
• 05:40 – Adding a column to a list
• 06:15 – My list for this solution
• 08:10 – The first flow
• 11:25 – Testing the first flow
• 12:26 – The second flow
• 17:01 – Testing the second flow
• 18:25 – Conclusion and wrap up

Very often terms such as Machine Learning, Artificial Intelligence, Deep Learning, Robotics, IoT, and Cloud are thrown around in leadership sessions as “silver bullets” or “easy buttons” that provide a competitive advantage.

While there is reason for the sizzle behind the hype, it’s not what we should focus on.

We should be focusing on Impact.

The cornerstone of Artificial Intelligence is Machine Learning, where historical data (which ever organisation has) is used to teach sophisticated algorithm or machines to solve everyday problems. Providing businesses with insights into what the future will hold. Sounds much like science fiction you tell me? Well not so much as you would think, these “machines” are readily available to the public in tools such as Scikit-learn, Tensorflow, jupyter notebook, Python and R.

In this deeplizard episode, learn how to prepare and process our own custom data set of sign language digits, which will be used to train our fine-tuned MobileNet model in a future episode.

VIDEO SECTIONS

• 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
• 00:40 Obtain the Data
• 01:30 Organize the Data
• 09:42 Process the Data
• 13:11 Collective Intelligence and the DEEPLIZARD HIVEMIND

Brian Blanchard joins Scott Hanselman to discuss Azure landing zones and how you can prepare your destination Azure environment—not only to receive migrating applications, but also to balance agility, governance, and security considerations.