Goto

Collaborating Authors

Intro to Deep Learning project in TensorFlow 2.x and Python - CouponED

#artificialintelligence

Welcome to the Course Introduction to Deep Learning with TensorFlow 2.0: In this course, you will learn advanced linear regression technique process and with this, you can be able to build any regression problem. Using this you can solve real-world problems like customer lifetime value, predictive analytics, etc. All the above-mentioned techniques are explained in TensorFlow. Problem Statement: A large child education toy company that sells educational tablets and gaming systems both online and in retail stores wanted to analyze the customer data. The goal of the problem is to determine the following objective as shown below.


Introduction to Deep Learning with TensorFlow 2.0

#artificialintelligence

Introduction to Deep Learning with TensorFlow 2.0 Advanced implementation of regression model and essential tasks to be performed like feature selection in TensorFlow 2.x Bestseller What you'll learn In this course, you will learn advanced linear regression technique process and with this you can able to build any regression problem. With this intuition we will work on project: Customer Revenue Prediction. Problem Statement: A large child education toy company which sells educational tablets and gaming systems both online and in retail stores wanted to analyse the customer data. The goal of the problem is determine the following objective as shown below. Data Analysis & Preprocessing: Analyze customer data and draw the insights w.r.t revenue and based on the insights we will do data preprocessing.


12 Best Courses to Learn Deep Learning

#artificialintelligence

A generative Adversarial Network (GAN) is a powerful algorithm of Deep Learning. Generative Adversarial Network is used in Image Generation, Video Generation, and Audio Generation. In short, GAN is a Robot Artist, who can create any kind of art perfectly. And in this Generative Adversarial Networks (GANs) Specialization, you will learn how to build basic GANs using PyTorch and advanced DCGANs using convolutional layers. You will use GANs for data augmentation and privacy preservation, survey GANs applications, and examine and build Pix2Pix and CycleGAN for image translation. There are 3 courses in this Specialization program where you will gain hands-on experience in GANs. Now, let's see all the 3 courses of this Specialization Program-


Artificial Neural Networks (ANN) with Keras in Python and R

#artificialintelligence

Artificial Neural Networks (ANN) with Keras in Python and R, Understand Deep Learning and build Neural Networks using TensorFlow 2.0 and Keras in Python and R Created by Start-Tech AcademyPreview this Course - GET COUPON CODE You're looking for a complete Course on Deep Learning using Keras and Tensorflow that teaches you everything you need to create a Neural Network model in Python and R, right? You've found the right Neural Networks course! After completing this course you will be able to: Identify the business problem which can be solved using Neural network Models. Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc. Create Neural network models in Python and R using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts How this course will help you?


Neural Networks in Python: Deep Learning for Beginners

#artificialintelligence

Preview this course - GET COUPON CODE You're looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in Python, right? You've found the right Neural Networks course! After completing this course you will be able to: Identify the business problem which can be solved using Neural network Models. Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc. Create Neural network models in Python using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts How this course will help you?