Free Certification Course Title: Intro to Deep Learning project in TensorFlow 2.x and Python
Advanced implementation of regression modeling techniques like lasso regression in TensorFlow
What you’ll learn:
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TensorFlow 2.0
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Gradient Descent Algorithm
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Create Pipeline regression model in TensorFlow
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Lasso Regression
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Feature Selection with lasso
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Programming in TensorFlow 2.0
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Selection of Penalty factor lambda
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Visualizing graph in TensorBoard
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Neuron or Perceptron Model Architecture
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Loss or Cost Function
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TensorFlow Keras API
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Linear Regression
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Create customized model in TensorFlow
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Exploratory Data Analysis
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Data Preprocessing
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Multiple Linear Regression in TensorFlow
Requirements:
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Beginner to Python
Who this course is for:
- Anyone who wants to build and train their own network
- Curious about data science
- Who want to learn Deep Learning
Description:
Welcome to the Course Introduction to Deep Learning with TensorFlow 2.0:
In this course, you will learn the 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
· 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
This course includes:
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5.5 hours on-demand video
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2 articles
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Full lifetime access
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Access on mobile and TV
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Assignments
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Certificate of completion
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