TensorFlow A Guide to TensorFlow: Building a Neural Network (Part 7) Uptil now we've learnt how to build simple machine learning models using tensorflow, This guide takes it to the next level, here we will code and run our own neural network.

TensorFlow A Guide to TensorFlow: Logistic Regression (Part 6) Logistic regression models the probability of the default class (e.g. the first class). For example, if we are modeling people’s gender as male or female from the length of their hair

TensorFlow A Guide to TensorFlow: Linear regression (Part 5) Linear regression is a way to find an equation that models a relationship between a dependent variable X and a explanatory variable Y.

TensorFlow A Guide to TensorFlow (Part 4) Transformation consists of the graph we've be using in our examples, it consists of an input placeholder, the input is fed in a product and a sum node. Their outputs are then added, the resultant is the output of the transformation block.

TensorFlow A Guide to TensorFlow (Part 3) It is important for us to create our operations and build our computation graph, irrespective of the available data. In other words we must have a provision to provide data dynamically from a client program, or a helper function. We do that with what is called a “placeholder”.

TensorFlow A Guide to TensorFlow (Part 2) TensorFlow Operations, also known as Ops, are nodes that perform computations on or with Tensor objects. After computation, they return zero or more tensors, which can be used by other Ops later in the graph...

TensorFlow A Guide to TensorFlow (Part 1) At the heart of a TensorFlow program is the computation graph described in code. A computation graph is essentially a series of functions chained together