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Created by tech.courses team, offered on Udemy
To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 3799 students which left 542 reviews at an average rating of 4.28, which is average.
We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 7 hours 16 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 7 hours 54 minutes.
This course currently has a bestcourses score of 6.3/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.
Updated for 2022!
Throughout the course we use house price data to ask ever more complicated questions; “can you predict the value of this house?”, “can you tell me if this house has a waterfront?”, “can you classify it as having 1, 2 or 3+ bedrooms?”. Each example builds on the one before it, to reinforce learning in easy and steady steps.
Machine Learning in TensorFlow.js provides you with all the benefits of TensorFlow, but without the need for Python. This is demonstrated using web based examples, stunning visualisations and custom website components.
This course is fun and engaging, with Machine Learning learning outcomes provided in bitesize topics:
Part 1 - Introduction to TensorFlow.js
Part 2 - Installing and running TensorFlow.js
Part 3 - TensorFlow.js Core Concepts
Part 4 - Data Preparation with TensorFlow.js
Part 5 - Defining a model
Part 6 - Training and Testing in TensorFlow.js
Part 7 - TensorFlow.js Prediction
Part 8 - Binary Classification
Part 9 - Multi-class Classification
Part 10 - Conclusion & Next Steps
What you will learn
- Deep Learning and Neural Network concepts
- Defining machine learning models
- How to install and run TensorFlowJS 3
- How TensorFlowJS 3 is optimised
- Training machine learning models
- Data preparation for machine learning
- How to make accurate predictions
- Linear regression
- Binary classification
- Multi-class classification
- Heatmap visualisation
- Scatter-plot visualisation
- Importing and normalising data
- How to manage memory in TensorFlowJS 3
- Tensor mathematics
- Saving machine learning models
- Inputting and outputting using a web browser
- Shuffling, and splitting data
- In-depth labs for practical development
- Some high school maths (but we give links if you need a refresher!)