Beginner’s Guide to Deep Learning with TensorFlow 2.x and Python

Beginner's Guide to Deep Learning with TensorFlow 2.x and Python, Feature Image

Data Science Anywhere, Sudhir G, Convolution Innovations

Last Updated on October 16, 2023 by GeeksGod

Course : Intro to Deep Learning project in TensorFlow 2.x and Python

Introduction to Deep Learning with TensorFlow 2.0

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.

What you will Learn

In this course, you will learn:

  • TensorFlow 2.x
  • Google Colab
  • Linear Regression
  • Gradient Descent Algorithm
  • Data Analysis
  • Regression
  • Feature Engineering and Selection with Lasso Regression
  • Model Evaluation

All the above-mentioned techniques are explained in TensorFlow. In this course, you will work on the Project Customer Revenue (Lifetime value) Prediction using Gradient Descent Algorithm

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.

  1. Data Analysis & Pre-processing:
  2. Analyze customer data and draw insights with respect to revenue. Based on the insights, we will perform data pre-processing. In this module, you will learn the following:

    • Necessary Data Analysis
    • Multi-collinearity
    • Factor Analysis
  3. Feature Engineering:
  4. In this module, you will learn:

    • Lasso Regression
    • Identify the optimal penalty factor
    • Feature Selection
  5. Pipeline Model
  6. Evaluation

We will start with the basics of TensorFlow 2.x to advanced techniques in it. Then we will dive into the intuition behind linear regression and optimization functions like gradient descent.

Enroll in this course now and gain in-depth knowledge of TensorFlow deep learning and how it can be applied to solve real-world problems. Don’t miss out on this opportunity to enhance your skills and advance your career in the field of deep learning.

Free Udemy Coupon:

If you are interested in learning TensorFlow deep learning and want to access free resources, be sure to check out the many Udemy courses available. With these courses, you can learn at your own pace and at no cost to you. So don’t wait, grab your Free Udemy Coupon now and start your journey into the world of deep learning.

By utilizing Free Udemy Coupon, you can access courses that cover a wide range of topics, including TensorFlow deep learning. Take advantage of this opportunity to gain valuable knowledge and skills without breaking the bank.

Why Learn TensorFlow Deep Learning?

TensorFlow is a widely popular platform for deep learning. By learning TensorFlow deep learning, you can gain expertise in building and training neural networks on large datasets. This skill is highly sought after in the field of artificial intelligence and can open up numerous career opportunities for you.

In today’s fast-paced world, businesses are constantly seeking ways to optimize their operations and improve decision-making. By leveraging deep learning techniques with TensorFlow, you can develop models that can process vast amounts of data, identify patterns, and make accurate predictions. This can have a significant impact on businesses, leading to increased efficiency and profitability.


In conclusion, learning TensorFlow deep learning is essential if you want to stay ahead in the field of artificial intelligence. With the right skills and knowledge, you can become a valuable asset to any organization by harnessing the power of deep learning to drive insights and make informed decisions.

So, why wait? Start your learning journey today with Free Udemy Coupon and master TensorFlow deep learning!

Udemy Coupon :


What you will learn :

1. TensorFlow 2.0
2. Gradient Descent Algorithm
3. Create Pipeline regression model in TensorFlow
4. Lasso Regression
5. Feature Selection with lasso
6. Programming in TensorFlow 2.0
7. Selection of Penalty factor lambda
8. Visualizing graph in TensorBoard
9. Neuron or Perceptron Model Architecture
10. Loss or Cost Function
11. TensorFlow Keras API
12. Linear Regression
13. Create customized model in TensorFlow
14. Exploratory Data Analysis
15. Data Preprocessing
16. Multiple Linear Regression in TensorFlow

100% off Coupon