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Jamiroquai - You Give Me Something (Official 4K Video)
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Lyrics
When I met you
You were so unique
You had a little thing I'd love to keep
Every movement
Carried much mystique
I knew right then I'd carry on
To you I knew my heart belongs
You know, you
You give me something
Something that nobody else can give
And my heart
Started thumping
You know now, you're the one I truly know I dig
Like the sunbeams from
A perfect summer day
Heaven only seems a step away
When I'm with you
I just celebrate
I'm hoping my message gets through
That there's never been someone like you
I had nobody
But on you I lean
'Cause you got these little things that I
I know I've never seen
You know now, you
You give me something
Something that nobody else has got
And this love
That I've been wanting
Oh baby, it's turning out to be too fast to stop
You know now, ooh
You give me something
Something that nobody else can give
See my heart
Has started thumping
You know babe
You're the one I truly know I dig
Ooh, will you give me something?
Ooh, will you give me something?
Ooh, will you give me something?
Ooh, will you give me something?
Ooh, will you give me something?
Ooh, will you give me something?
Ooh, will you give me something?
Ooh, will you give me something?
You give me something that nobody else can give
You give me something that nobody else can give
This is my solution to predictOneVsAll.m function in Programming assignment 3 from the famous Machine Learning course by Andrew Ng.
Github: https://github.com/AladdinPerz....on/Courses/tree/mast
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INTRODUCTION TO DEEP LEARNING
0:00:00 Welcome
0:05:31 What is a Neural Network
0:12:48 Supervised Learning with Neural Network
0:21:17 Why is Deep Learing taking off
0:31:38 About this course
0:34:06 Geoffrey Hinton Interview
NEURAL NETWORKS BASICS
1:14:28 Binary Classification
1:22:52 Logistic Regression
1:28:51 Logistic Regression Cost Function
1:37:03 Gradient Descent
1:48:26 Derivatives
1:55:37 More Derivative Example
2:06:04 Computation Graph
2:09:38 Derivatives With a Computation Graph
2:24:12 Logistic Regression Gradient Descent
2:30:54 Gradient Descent on m Examples
2:38:55 Vectorization
2:46:59 More Vectorization Examples
2:53:18 Vectorization Logistic Regression
3:00:50 Vectorization Logistic Regression Gradient Output
3:10:28 Broadcasting in PYthon
3:21:34 A Note on Python Numpy Vectors
3:28:23 Quick tour of jupyter iPython Notebooks
3:32:06 Explanation of Logistics Regression Cost Function (optional)
3:39:21 Pieter Abbeel Interview
SHALLOW NEURAL NETWORKS
3:55:25 Neural Network Overview
3:59:51 Neural Network Representation
4:05:05 computing a Neural Network's output
4:15:03 Vectorizing Across Multiple Examples
4:24:09 Explantion for Vectorized Implementation
4:31:46 Activation Functions
4:42:43 Why do you need Non-Linear Activation Functions
4:48:19 Derivatives of Activation Functions
4:56:16 Gradient Descent for Neural Networks
5:06:14 Backpropagation Intuition (Optional)
5:22:02 Random Initialization
5:30:00 Ian Goodfellow Interview
DEEP NEURAL NETWORKS
5:44:56 Deep L-layer Neural Network
5:50:47 Forward Propagation in a Deep Network
5:58:02 Getting your Matrix Dimentions Right
6:09:12 Why Deep Representations
6:19:46 Building Blocks of Deep Neural Networks
6:28:19 Forward and Backward propagation
6:38:49 Parameters vs Hyperparameters
6:46:06 What does this have to do with brain
By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications.
⭐ Important Notes ⭐
⌨️ The creator of this course is Deeplearning.ai (Andrew Ng)
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Releasing live on Facebook, Sunday, August 26 at 8PM EST, FULLSTERKUR is the third documentary in a collection of films produced by Rogue Fitness, exploring strength culture around the world, connected specifically by the ancient tradition of stone lifting.
Nestled at the doorstep of the Arctic Circle, the country of Iceland is uniquely acquainted with the relationship between strength and survival. For hundreds of years, men and women were challenged to overcome harsh weather and endless winter nights by developing their own distinct physical and mental fortitude—passed down from the age of the Vikings, and iconically represented by the lifting of heavy stones. Today, on an island with a population of just over 300,000, a disproportionate number of the world’s greatest strength athletes still call Iceland home.
The film features some of the modern stars of Iceland strength, including Magnus Ver Magnuson, Hafthor Bjornsson, and Annie Thorisdottir. But it also sheds light on strength culture’s early roots in the region, from the traditions of the Vikings and Sagas to the lives of farmers and fishermen.