What you’ll learn
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Get a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning
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Build an end-to-end Image recognition project in R
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Learn usage of Keras and Tensorflow libraries
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Use Artificial Neural Networks (ANN) to make predictions
After completing this course you will be able to:
- Identify the Image Recognition problems which can be solved using CNN Models.
- Create CNN models in R using Keras and Tensorflow libraries and analyze their results.
- Confidently practice, discuss and understand Deep Learning concepts
- Have a clear understanding of Advanced Image Recognition models such as LeNet, GoogleNet, VGG16 etc.
Who this course is for:
- People pursuing a career in data science
- Working Professionals beginning their Deep Learning journey
- Anyone curious to master image recognition from Beginner level in short span of time
Can I download Image Recognition for Beginners using CNN in R Studio course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Image Recognition for Beginners using CNN in R Studio course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.com
Note: 100% OFF Udemy coupon codes are valid for maximum 3 days only. Look for "ENROLL NOW" button at the end of the post.
Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
