TensorFlow ML: Mastering TensorFlow in 60 Minutes

TensorFlow ML: Mastering TensorFlow in 60 Minutes
Published 6/2024
Duration: 1h22m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 403 MB
Genre: eLearning | Language: English

Mastering TensorFlow Basics in 60 Minutes: From Data Prep to Model Deployment

What you'll learn
Build a machine learning model
Understand data preprocessing
Understand the architecture of a model
Understand the process behind training a model

Requirements
An understanding of basic programming concepts (variables, arrays, datatypes) would help but is not essential to follow along with the course.

Description
In this intensive one-hour course, you'll dive headfirst into the world of machine learning using TensorFlow and Google Colab. No pit stops—just pure acceleration!
What You'll Cover:
TensorFlow Basics:
Understand the core concepts, from defining layers to training models.
Google Colab Mastery:
Leverage Colab's cloud-based environment for seamless development.
Data Prep Express:
Quickly preprocess your data without detours.
Model Construction:
Design and build neural networks like a seasoned pro.
Training and Evaluation:
Witness your model learn, iterate, and fine-tune for optimal performance.
Why Take This Course?
Speedy Results:
Get up to speed in just one hour.
Practical Skills:
Apply what you learn to real-world problems.
No Pit Stops:
We're all about efficiency here!
Prerequisites:
Basic Python knowledge (if you can write a
for
loop, you're set!)
Curiosity and a dash of determination
Ready to accelerate your ML journey? Buckle up!
Whether you're a data enthusiast, a developer, or a curious learner, this course is your express ticket to mastering machine learning essentials. Let's hit the road!
Your course instructor is me Adam Cole, a professional software engineer with 5 years working on enterprise level applications. Feel free to send me any questions on LinkedIn at Adam Cole
Adam Cole BSc MBCS
.
Who this course is for:
Anyone that wants to build an ML model for the first time.

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