TensorFlow has several high-level libraries allowing us to reduce time modeling all with core code. TF Estimator makes it simple … More

# Tag: Python

# TensorFlow Way for Linear Regression

In my two previous posts, we saw how we can perform Linear Regression using TensorFlow, but I’ve used Linear Least … More

# Cholesky Decomposition for Linear Regression with TensorFlow

Although Linear Least Squares Regression is simple and precise, it can be inefficient when matrices get very large. Cholesky decomposition … More

# Linear Least Squares Regression with TensorFlow

Linear Least Squares Regression is by far the most widely used regression method, and it is suitable for most cases … More

# Classification Loss Functions (Part II)

In my previous post, I mentioned 3 loss functions, which are mostly intended to be used in Regression models. This … More

# Loss Functions (Part 1)

Implementing Loss Functions is very important to machine learning algorithms because we can measure the error from the predicted outputs … More

# Declaring tensors in TensorFlow

[Requirement: Tensorflow and NumPy installed on Python +3.5] [Requirement: import tensorflow as tf] [Requirement: import numpy as np] Tensors are … More