Mammoth Interactive
Well done!!!!!! I found it the BEST source for me out of many to learn how to implement AI project due the facts it starts from the very basics of Python and TensorFlow and assumes no prior knowledge (or almost no prior knowledge) which should not be taken for granted since other courses do so. The instructor is wonderful and explains all the concepts wonderfully! Thank you so much! helped me a lot!
Very easy to understand. Loving it so far! – Arthur G.
This course was funded by a wildly successful Kickstarter.
Let’s learn how to perform automated image recognition! In this course, you learn how to code in Python, calculate linear regression with TensorFlow, and perform CIFAR 10 image data and recognition. We interweave theory with practical examples so that you learn by doing.
AI is code that mimics certain tasks. You can use AI to predict trends like the stock market. Automating tasks has exploded in popularity since TensorFlow became available to the public (like you and me!) AI like TensorFlow is great for automated tasks including facial recognition. One farmer used the machine model to pick cucumbers!
Join Mammoth Interactive in this course, where we blend theoretical knowledge with hands–on coding projects to teach you everything you need to know as a beginner to image recognition.
Instructor Details
Courses : 91
Specification: Build and train a data model to recognize objects in images!
|
6 reviews for Build and train a data model to recognize objects in images!
Add a review
| Price | $14.99 |
|---|---|
| Provider | |
| Duration | 8.5 hours |
| Year | 2019 |
| Level | Beginner |
| Language | English |
| Certificate | Yes |
| Quizzes | No |
$14.99
Kuldeep Singh –
Very Good Course
Daniel Mayusa Dewa –
Easy to follow, I’d buy more when there are more advance course after this !
Acting Sub Lt. Petchara Inthanon –
It ok . but This version very old version.
Tanmay Rajoria –
Very informative and experience rich
Keegan Bryan –
Overall course was helpful for student with limited knowledge of this subject, however the course starts and ends with unnecessary animations. The course section arrangement could be better as the small project was done ahead of proper explanation on everything used in project thus since the lecturer already explained in the project section, other section might not be as useful. Note that this course require : Tensorflow < 2.0, if using tensorflow gpu & has Nvidia Discrete GPU use Nvidia Cuda 10 and download separately Nvidia cuDNN. Luckily the lecturer remind to download any library mentioned in this course, otherwise require some Google search before able to complete the course.
Ananyaja Debadipta –
Nice Course