JavaScript JavaScript: Async and Promises JavaScript is designed for the web, that means it's supposed to be asynchronous. This means, you can have two lines of code (L1 followed by L2), where L1 schedules some task to be run in the future, but L2 runs before that task completes.

JavaScript Over Explained - JavaScript and V8 Twenty years ago JavaScript was just another Turing-complete language that was used to create annoying pop-ups and maybe some fancy animations, but today this has largely changed.

Docker Docker Networking Explained One of the reasons Docker containers and services are so powerful is that you can connect them together, or connect them to non-Docker workloads. Therefore, there is a need for powerful networking elements that can support various complex use cases.

Node An Introduction to Node.js Node is an open source and cross platform runtime environment for running javascript code

Docker An Introduction to Docker Docker lets you package your application with everything it needs, from the operating system upwards, into a single unit that you can share and run on any computer that has Docker

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

Machine Learning Understanding Neural Networks (And How They Work) Artificial Neural Networks are class of a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data...

Machine Learning Understanding Gradient Descent At a theoretical level, gradient descent is an algorithm that minimizes functions.

TensorFlow Installing TensorFlow on Windows 10 TensorFlow is an open source software library for machine intelligence and numerical computation using data flow graphs. TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in