1598424619
Welcome to DataFlair Keras Tutorial series. This chapter explains how to compile, evaluate and make predictions from Model in Keras.
After defining our model and stacking the layers, we have to configure our model. We do this configuration process in the compilation phase.
Before training the model we need to compile it and define the loss function, optimizers, and metrics for prediction.
We compile the model using .compile() method.
model.compile ( optimizer, loss, metrics, loss_weights, sample_weight_mode, weighted_metrics, target_tensors)
Optimizer, loss, and metrics are the necessary arguments.
Keras provides various loss functions, optimizers, and metrics for the compilation phase.
#keras evaluate #keras predict #model in keras #keras
1598424619
Welcome to DataFlair Keras Tutorial series. This chapter explains how to compile, evaluate and make predictions from Model in Keras.
After defining our model and stacking the layers, we have to configure our model. We do this configuration process in the compilation phase.
Before training the model we need to compile it and define the loss function, optimizers, and metrics for prediction.
We compile the model using .compile() method.
model.compile ( optimizer, loss, metrics, loss_weights, sample_weight_mode, weighted_metrics, target_tensors)
Optimizer, loss, and metrics are the necessary arguments.
Keras provides various loss functions, optimizers, and metrics for the compilation phase.
#keras evaluate #keras predict #model in keras #keras
1595422560
Welcome to DataFlair Keras Tutorial. This tutorial will introduce you to everything you need to know to get started with Keras. You will discover the characteristics, features, and various other properties of Keras. This article also explains the different neural network layers and the pre-trained models available in Keras. You will get the idea of how Keras makes it easier to try and experiment with new architectures in neural networks. And how Keras empowers new ideas and its implementation in a faster, efficient way.
Keras is an open-source deep learning framework developed in python. Developers favor Keras because it is user-friendly, modular, and extensible. Keras allows developers for fast experimentation with neural networks.
Keras is a high-level API and uses Tensorflow, Theano, or CNTK as its backend. It provides a very clean and easy way to create deep learning models.
Keras has the following characteristics:
The following major benefits of using Keras over other deep learning frameworks are:
Before installing TensorFlow, you should have one of its backends. We prefer you to install Tensorflow. Install Tensorflow and Keras using pip python package installer.
The basic data structure of Keras is model, it defines how to organize layers. A simple type of model is the Sequential model, a sequential way of adding layers. For more flexible architecture, Keras provides a Functional API. Functional API allows you to take multiple inputs and produce outputs.
It allows you to define more complex models.
#keras tutorials #introduction to keras #keras models #keras tutorial #layers in keras #why learn keras
1623223443
Predictive modeling in data science is used to answer the question “What is going to happen in the future, based on known past behaviors?” Modeling is an essential part of data science, and it is mainly divided into predictive and preventive modeling. Predictive modeling, also known as predictive analytics, is the process of using data and statistical algorithms to predict outcomes with data models. Anything from sports outcomes, television ratings to technological advances, and corporate economies can be predicted using these models.
#big data #data science #predictive analytics #predictive analysis #predictive modeling #predictive models
1591861777
A model is the basic data structure of Keras. Keras models define how to organize layers. In this article, we will discuss Keras Models and its two types with examples. We will also learn about Model subclassing through which we can create our own fully-customizable models.
Models in keras are available in two types:
#keras tutorials #functional api in keras #keras models #models in keras
1607579145
In this video on Keras, you will understand what is Keras and why do we need it, how to compose different models in Keras like the Sequential model and functional model, and later on how to define the inputs, how to connect layers over, and finally hands-on demo.
Why Keras is important
Keras is an Open Source Neural Network library written in Python that runs on top of Theano or Tensorflow. It is designed to be modular, fast, and easy to use. Keras is very quick to make a network model. If you want to make a simple network model with a few lines, Keras can help you with that.
Call Our Course Advisors IND: +91-7022374614 US: 1-800-216-8930 (Toll-Free) sales@intellipaat.com
Link: https://www.youtube.com/watch?v=nS1J-2uoKto
#keras tutorial for beginners #what is keras #keras sequential model #keras training