FREE FOREVER Neural Networks Made Easy | UDEMY

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Requirements

• Be able to code in Python with NumPy and Pandas
  

DescriptionWanna understand deep learning and neural networks so well, you could code them from scratch? In this course, we'll do exactly that.
The course starts by motivating and explaining perceptrons, and then gradually works its way toward deriving and coding a multiclass neural network with stochastic gradient descent that can recognize hand-written digits from the famous MNIST dataset.
Course Goals
This course is all about understanding the fundamentals of neural networks. So, it does not discuss TensorFlow, PyTorch, or any other neural network libraries. However, by the end of this course, you should understand neural networks so well that learning TensorFlow and PyTorch should be a breeze!
Challenges
In this course, I present a number of coding challenges inside the video lectures. The general approach is, we'll discuss an idea and the theory behind it, and then you're challenged to implement the idea / algorithm in Python. I'll discuss my solution to every challenge, and my code is readily available on github.
Prerequisites
In this course, we'll be using Python, NumPy, Pandas, and good bit of calculus. ..but don't let the math scare you. I explain everything in great detail with examples and visuals.
If you're rusty on your NumPy or Pandas, check out my free courses Python NumPy For Your Grandma and Python Pandas For Your Grandpa.
Who this course is for:

• People interested in learning how neural networks work
  

t h a n k s

[331]

Don't forget to LIKE the thread please
All coupons are date and user limited, be fast!

Show ContentSpoiler:

Requirements

• Be able to code in Python with NumPy and Pandas
  

DescriptionWanna understand deep learning and neural networks so well, you could code them from scratch? In this course, we'll do exactly that.
The course starts by motivating and explaining perceptrons, and then gradually works its way toward deriving and coding a multiclass neural network with stochastic gradient descent that can recognize hand-written digits from the famous MNIST dataset.
Course Goals
This course is all about understanding the fundamentals of neural networks. So, it does not discuss TensorFlow, PyTorch, or any other neural network libraries. However, by the end of this course, you should understand neural networks so well that learning TensorFlow and PyTorch should be a breeze!
Challenges
In this course, I present a number of coding challenges inside the video lectures. The general approach is, we'll discuss an idea and the theory behind it, and then you're challenged to implement the idea / algorithm in Python. I'll discuss my solution to every challenge, and my code is readily available on github.
Prerequisites
In this course, we'll be using Python, NumPy, Pandas, and good bit of calculus. ..but don't let the math scare you. I explain everything in great detail with examples and visuals.
If you're rusty on your NumPy or Pandas, check out my free courses Python NumPy For Your Grandma and Python Pandas For Your Grandpa.
Who this course is for:

• People interested in learning how neural networks work
  

thank you for sharing

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Don't forget to LIKE the thread please
All coupons are date and user limited, be fast!

Show ContentSpoiler:

Requirements

• Be able to code in Python with NumPy and Pandas
  

DescriptionWanna understand deep learning and neural networks so well, you could code them from scratch? In this course, we'll do exactly that.
The course starts by motivating and explaining perceptrons, and then gradually works its way toward deriving and coding a multiclass neural network with stochastic gradient descent that can recognize hand-written digits from the famous MNIST dataset.
Course Goals
This course is all about understanding the fundamentals of neural networks. So, it does not discuss TensorFlow, PyTorch, or any other neural network libraries. However, by the end of this course, you should understand neural networks so well that learning TensorFlow and PyTorch should be a breeze!
Challenges
In this course, I present a number of coding challenges inside the video lectures. The general approach is, we'll discuss an idea and the theory behind it, and then you're challenged to implement the idea / algorithm in Python. I'll discuss my solution to every challenge, and my code is readily available on github.
Prerequisites
In this course, we'll be using Python, NumPy, Pandas, and good bit of calculus. ..but don't let the math scare you. I explain everything in great detail with examples and visuals.
If you're rusty on your NumPy or Pandas, check out my free courses Python NumPy For Your Grandma and Python Pandas For Your Grandpa.
Who this course is for:

• People interested in learning how neural networks work
  

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