machine learning

TensorFlow has several high-level libraries allowing us to reduce time modeling all with core code. TF Estimator makes it simple to create and train models for training, evaluating, predicting and exporting. TF Estimator provides 4 main functions on any kind of estimator: estimator.fit() estimator.evaluate() estimator.predict() estimator.export() All predefined estimators are...

In my previous post, I mentioned 3 loss functions, which are mostly intended to be used in Regression models. This time, I’m going to talk about Classification Loss Functions, which are going to be used to evaluate loss when predicting categorical outcomes. Let’s consider the following vector to help us...

Implementing Loss Functions is very important to machine learning algorithms because we can measure the error from the predicted outputs to the target values. Algorithms get optimized by evaluating outcomes depending on a specified loss function, and TensorFlow works in this way as well. We can think on Loss Functions...

Perceptron is a simple algorithm which, given an input vector x of m values (x1, x2, …, xm), outputs either 1 (ON) or 0 (OFF), and we define its function as follows: Here, ω is a vector of weights, ωx is the dot product, and b is the bias. This...

Matrices are the basic elements we use to interchange data through computational graphs. In general terms, a tensor can de defined as a matrix, so you can refer to Declaring tensors in TensorFlow in order to see the options you have to create matrices. Let’s define the matrices we are...

Usually, when we start using TensorFlow, it’s very common to think that defining variables is just as trivial as a HelloWorld program, but understanding how variables (and placeholders) work under the hood is very important to understand more complex concepts because those concepts heavily use variables/placeholders; and, if we don’t...

[Requirement: Tensorflow and NumPy installed on Python +3.5][Requirement: import tensorflow as tf][Requirement: import numpy as np] Tensors are the primary data structure we use in TensorFlow, and, as Wikipedia describes them, “tensors are geometric objects that describe linear relations between geometric vectors, scalars and other tensors”. Tensors can be described...