First Order Logic
· The prepositional logic only deals with the facts, that may be true or false. · The first order logic assumes that the world contains objects, relations and functions. Syntax for first…
Logic Representation
Facts are the general statements that may be either True or False. Thus, logic can be used to represent such simple facts. To build a Logic-based representation: · User has to define…
What is Knowledge Representation?
· Artificial intelligence is a system that is concerned with the study of understanding, designing and implementing the ways, associated with knowledge representation to computers. · In any intelligent system, representing the knowledge is…
Heuristics Search & Game Playing in AI
What is Heuristic? · The word heuristic is derived from the Greek word heuriskein, which means to find or to discover. · Heuristic search can be implemented by using a thumb rule, a judgment or…
What is TensorBoard
Tensorboard is the interface used to visualize the graph and other tools to understand, debug, and optimize the model. Example The image below comes from the graph you will generate…
Creating operator
Some Useful TensorFlow operators You know how to create a tensor with TensorFlow. It is time to learn how to perform mathematical operations. TensorFlow contains all the basic operations. You…
Shape of tensor
When you print the tensor, TensorFlow guesses the shape. However, you can get the shape of the tensor with the shape property. Below, you construct a matrix filled with a…
What is a Tensor?
Tensorflow's name is directly derived from its core framework: Tensor. In Tensorflow, all the computations involve tensors. A tensor is a vector or matrix of n-dimensions that represents all types of data. All values in…
What is Jupyter Notebook?
A Jupyter notebook is a web application that allows the user to write codes and rich text elements. Inside the Notebooks, you can write paragraph, equations, title, add links, figures…
TensorFlow Versions
TensorFlow supports computations across multiple CPUs and GPUs. It means that the computations can be distributed across devices to improve the speed of the training. With parallelization, you don't need…
