What you'll learn
- The fundamentals of deep learning, including how to build and train multilayer perceptron’s
- cloud tools and deep learning libraries
- Apply a deep learning package to sequential data, then train and tune models
Who is this course for
- Beginners interested in deep learning
- People interested in machine language
- People from data science background willing to enhance their skills
After finishing this course, you will ace all things related to deep learning.
With this, you can get free access to
- Course Materials for Life
- Expertise in deep learning and machine language
About Us
Over 100,000 students have received instruction from this online academy in topics including Lift Style, Fitness Training, Cyber Security, Ethical Hacking, Facebook Ads, SEO, Email Marketing, eCommerce, Business Investing, Social Media Marketing, Launching Your Own Business, and Marketing/Ad Agency!
We provide a wide variety of top-notch online courses that educate through real-world examples from subject matter experts and tried-and-true research, all supported by top-notch, studio vocally narrated videos! Teaching practical life skills, which are crucial in today's environment, is the focus.
Every course offered by this online learning academy is instructed by subject-matter specialists who genuinely love what they do and want to share it with others.
Course Curriculum
- 001. Welcome to AML Specialization! (2:49)
- 002. Course Intro (6:02)
- 003. Linear regression (9:58)
- 004. Linear classification (10:50)
- 005. Gradient descent (5:04)
- 006. Overfitting problem and model validation (6:56)
- 007. Model regularization (5:20)
- 008. Stochastic gradient descent (5:40)
- 009. Gradient descent extensions (9:58)
- 010. Multilayer perceptron (MLP) (12:36)
- 011. Chain rule (7:30)
- 012. Backpropagation (9:01)
- 013. Efficient MLP implementation (13:08)
- 014. Other matrix derivatives (5:54)
- 015. What is TensorFlow (10:54)
- 016. Our first model in TensorFlow (10:11)
- 017. What Deep Learning is and is not (8:37)
- 018. Deep learning as a language (6:59)
- 019. Motivation for convolutional layers (11:14)
- 020. Our first CNN architecture (10:59)
- 021. Training tips and tricks for deep CNNs (14:48)
- 022. Overview of modern CNN architectures (8:19)
- 023. Learning new tasks with pre-trained CNNs (5:16)
- 024. A glimpse of other Computer Vision tasks (8:17)
- 025. Unsupervised learning what it is and why bother (5:57)
- 026. Autoencoders 101 (5:34)
- 027. Autoencoder applications (9:42)
- 028. Autoencoder applications image generation, data visualization & more (7:19)
- 029. Natural language processing primer (10:10)
- 030. Word embeddings (13:21)
- 031. Generative models 101 (7:31)
- 032. Generative Adversarial Networks (10:05)
- 033. Applications of adversarial approach (11:08)
- 034. Motivation for recurrent layers (7:36)
- 035. Simple RNN and Backpropagation (8:23)
- 036. The training of RNNs is not that easy (7:19)
- 037. Dealing with vanishing and exploding gradients (9:02)
- 038. Modern RNNs LSTM and GRU (11:30)
- 039. Practical use cases for RNNs (13:17)
Frequently Asked Questions
When does the course start and finish?
The course has begun and will never stop! You set the start and end dates for this entirely self-paced online course.
How long do I have access to the course?
Lifetime access—how does that sound? You receive unrestricted access to this course after registering for as long as you like, on any device you own.
Do I get a certificate?
Yes, when you complete the course, you will receive a certificate of completion which you can happily add to your resume or LinkedIn profile.
Can I cancel my subscription?
Yes you can. You have a 15-days money-back guarantee.
