An end-to-end open-source platform for Machine Learning. Before we start with TensorFlow, we will need to know what machine learning and deep learning technologies are.
Before we start with TensorFlow, we will need to know what machine learning and deep learning technologies are. Machine Learning is an application of Artificial Intelligence which provides automation to systems where Machine or System can learn on its own and It may improve based on previous experience and it can be done without external programming. Deep Learning is the next part of machine learning. Which more focuses on algorithms that are inspired by the structure and functioning of the human brain. Deep learning models sometimes achieve higher accuracies because it uses neural networks to perform tasks. This is where we use TensorFlow because it largely deals with deep neural networks.
TensorFlow
Tensorflow is an open-source library developed by Google and nowadays it has become a more powerful tool to run complex computations. Deep learning has two libraries named Keras and PyTorch which are now replaced by TensorFlow.Because TensorFlow has faster compilation time than these libraries. In reality, Tensorflow performs a huge amount of computations it deals with a higher amount of data such as images. It accepts data in multidimensional arrays called *“Tensors”. *Tensorflow handles data in the form of graphs by creating neural networks whenever there is a necessity. It also facilitates APIs (Application programming interfaces that are used for connecting different codes or applications)for machine learning. once accessing of data is done then there is no stopping TensorFlow automatically takes care of the rest of the things from creating a required neural network, parsing required data. In Tf computation in each iteration represented by the data flow graph because it does not follow the traditional programming approach.TensorFlow works fine on both CPU and GPU(capability to do higher computations and it contains higher power than CPU)computing devices. So using TensorFlow makes life easier.
data-science neural-networks machine-learning deep-learning tensorflow data analysis
Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
This full course introduces the concept of client-side artificial neural networks. We will learn how to deploy and run models along with full deep learning applications in the browser! To implement this cool capability, we’ll be using TensorFlow.js (TFJS), TensorFlow’s JavaScript library.
A practical and hands-on example to know how to use transfer learning using TensorFlow. We will learn how to use transfer learning for a classification task.
The past few decades have witnessed a massive boom in the penetration as well as the power of computation, and amidst this information.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant