Course Outline

Introduction

TensorFlow Overview

  • What is TensorFlow?
  • TensorFlow features

What is AI

  • Computational Psychology
  • Computational Philosophy

Machine Learning

  • Computational learning theory
  • Computer algorithms for computational experience

Deep Learning

  • Artificial neural networks
  • Deep learning vs. machine learning

Preparing the Development Environment

  • Installing and configuring TensorFlow

TensorFlow Quick Start

  • Working with nodes
  • Using the Keras API

Fraud Detection

  • Reading and writing to data
  • Preparing features
  • Labeling data
  • Normalizing data
  • Splitting data into test data and training data
  • Formatting input images

Predictions and Regressions

  • Loading a model
  • Visualizing predictions
  • Creating regressions

Classifications

  • Building and compiling a classifier model
  • Training and testing the model

Summary and Conclusion

Requirements

  • Python programming experience

Audience

  • Data Scientists
  14 Hours
 

Testimonials

Related Courses

Scaling Data Analysis with Python and Dask

  14 hours

Data Analysis with Python, Pandas, and Numpy

  14 hours

Accelerating Python Pandas Workflows with Modin

  14 hours

Machine Learning with Python and Pandas

  14 hours

FARM (FastAPI, React, and MongoDB) Full Stack Development

  14 hours

Developing APIs with Python and FastAPI

  14 hours

Web application development with Flask

  14 hours

Advanced Flask

  14 hours

Build REST APIs with Python and Flask

  14 hours

Kivy: Building Android Apps with Python

  7 hours

Game Development with PyGame

  7 hours

GUI Programming with Python and PyQt

  21 hours

Scientific Computing with Python SciPy

  7 hours

GUI Programming with Python and Tkinter

  14 hours

Web Development with Web2Py

  28 hours