What you'll learn

0

Gradient Descent Algorithm

Create Pipeline regression model in TensorFlow

Lasso Regression

Feature Selection with lasso

Programming in 0

Selection of Penalty factor lambda

Visualizing graph in TensorBoard

Neuron or Perceptron Model Architecture

Loss or Cost Function

TensorFlow Keras API

Linear Regression

Create customized model in TensorFlow

Exploratory Data Analysis

Data Preprocessing

Multiple Linear Regression in TensorFlow

Requirements

Bner to Python

Description

In this course, you will learn advanced linear regression technique process and with this you can able to build any regression problem. Starting from

x

Linear Regression

Gradient Descent Algorithm

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 detee 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. In this module you will learn the following.

Necessary Data Analysis

Multi-colinearity

Factor Analysis

Feature Eeering:

Lasso Regression

Identify optimal penalty factor

Feature Selection

Pipeline Model

Evaluation

We will start with basic of tensorflow 2.x to advanced techniques in it. Then we drive into intuition behind linear regression and optimization function like gradient descent.

Who this course is for:

Anyone who want to build and train their own network

Curious of data science

Who want to learning Deep Learning



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