Title

Build A Real World Deep Learning Solution: Practical Guide

Build a deep learning project from scratch and understand the core concepts

Udemy
platform
English
language
Software Engineering
category
Build A Real World Deep Learning Solution: Practical Guide
56
students
3.5 hours
content
Apr 2020
last update
$19.99
regular price

What you will learn

Learn to build a real world deep learning solution

Understand core concepts of Deep learning

Why take this course?

🎓 Course Title: Build A Real World Deep Learning Solution: Practical Guide


🚀 Course Headline: Build a deep learning project from scratch and understand the core concepts!


Course Description:

Deep learning, a subset of artificial intelligence (AI), has revolutionized the way machines learn and make decisions. With its applications spanning across various industries, deep learning has become a cornerstone in the field of machine learning. 🤖

From self-driving cars to facial recognition systems, deep learning technologies are enabling devices to interpret complex data from the world around us. The retail sector is no exception; big mart sale predictions are being shaped by this powerful technique, optimizing inventory and sales strategies in real time.

In this comprehensive course, you will embark on a journey to understand and build a real-world deep learning solution using TensorFlow. 🌐

What You Will Learn:

  • Introduction to Deep Learning: Gain a foundational understanding of deep learning and its place within AI.
  • Core Concepts Explained: Dive into neural networks, logistic regression, and other machine learning concepts with clarity and depth.
  • Data Science Hypotheses: Learn how to formulate hypotheses that enable you to approach data science problems systematically.
  • Data Exploration & Visualization: Master the art of exploring and visualizing data to uncover insights and patterns.
  • Data Regression Techniques: Explore regression techniques necessary for predicting continuous outcomes, such as sales figures.

Hands-On Learning Experience:

  • Hypothetical Scenario: Utilize a hypothetical scenario of tracking big mart sales to apply deep learning principles in practice.
  • Real-World Data Preparation: Learn the steps for extracting, pre-processing, and preparing data from real-world sources like Big Mart datasets.
  • Building & Testing Models: Develop and test a predictive model that can forecast sales values for various products at a big mart.
  • Final Project: By the end of this course, you will have built a fully functional deep learning model tailored to real-world applications.

Who Is This Course For?

This course is ideal for:

  • Aspiring data scientists and machine learning enthusiasts looking to master deep learning.
  • Professionals in retail who want to understand how deep learning can add value to their sales prediction processes.
  • Individuals interested in leveraging AI to solve complex problems across various industries.

Course Highlights:

  • Step-by-Step Approach: Learn through a structured curriculum that takes you from basics to advanced concepts without skipping essential steps.
  • Real-World Data Sets: Work with real-world datasets, including the famous Iris flower dataset and Big Mart data, to apply deep learning in practical scenarios.
  • Hands-On Projects: Engage with meaningful projects that reflect the challenges faced by professionals in the field.
  • Expert Guidance: Learn from industry experts who bring years of experience in deep learning and machine learning.

👩‍🏫 Get Started Today! 🏃‍♂️

By enrolling in this course, you're taking the first step towards mastering deep learning and building predictive models that can have a real-world impact. Don't miss out on the opportunity to transform data into actionable insights with deep learning. 🌟


Ready to dive into the world of deep learning? Click here to enroll in the Build A Real World Deep Learning Solution: Practical Guide course and begin your journey towards becoming a deep learning expert today! 🚀📚

Coupons

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31/03/202178% OFF
expired

Related Topics

2901574
udemy ID
23/03/2020
course created date
22/05/2020
course indexed date
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