In a previous post, I shared about the biggest failures in predicting the future, specially when it comes to the technology domain. It’s a fun post to check. In 1964, Sir Arthur Clarke said the following famous quote:

Trying to predict the future is a discouraging and hazardous occupation, because…

Simply speaking, a hash function is a mathematical function that takes any input size and convert it to a fixed output size. Consider this simple hash function** H(X) = Last digit of (X)**

- H(1234) = 4.
- H(12567) = 7.
- H(127) = 7.
- H(1111111111) = 1.
- H(24)=4.
- H(24)=4.

So no matter…

In a previous post, we explained the mechanics behind Neural networks. In this post we will show a basic implementation in pure Numpy, and in TensorFlow.

As we previously explain, neural networks execution have 4 main steps:

- Forward step (where we go from inputs to outputs)
- Loss function (where we…

*This post is meant to be read after:*

For all the previously introduced layers, the same output will be generated if we repeat the same input several times. For…

After introducing neural networks and linear layers, and after stating the limitations of linear layers, we introduce here the dense (non-linear) layers.

In general, they have the same formulas as the linear layers wx+b, but the end result is passed through a non-linear function called **Activation function**.

`y = f(w*x…`

Many people perceive Neural Networks as black magic. We all have sometimes the tendency to think that there is no rationale or logic behind the Neural Network architecture. …

Machine learning (ML) is one of the hottest fields in computer science. So many people are jumping with the fake idea that it’s just about running 10 lines of python code, and expecting things to work by magic in any situation. This blog post is about all the things I…

Machine learning (ML) is one of the hottest fields in computer science. So many people are jumping with the fake idea that it’s just about running 10 lines of python code, and expecting things to work by magic in any situation. This blog post is about all the things I…

The dimension of a mathematical object is the number of **independent** **variables** needed to fully describe it. A point has 0 dimensions. A line has 1 dimension, a square has 2 dimensions and a cube has 3 dimensions. On a line we need one variable, let’s say the distance from…

The dimension of a mathematical object is the number of **independent** **variables** needed to fully describe it. A point has 0 dimensions. A line has 1 dimension, a square has 2 dimensions and a cube has 3 dimensions. On a line we need one variable, let’s say the distance from…