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The Complete Deep Learning Course 2021 With 7+ Real Projects

Learn how to use Google's Deep Learning Framework - TensorFlow with Python! Solve problems with cutting edge techniques!
5.0
5.0/5
(5 reviews)
60 students
Created by Hoang Quy La

10.0

CourseMarks Score®

9.9

Freshness

9.5

Feedback

10.0

Content

Platform: Udemy
Price: $11.99
Video: 16h 38m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

10.0 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.9 / 10
This course was last updated on 3/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

9.5 / 10
We analyzed factors such as the rating (5.0/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

10.0 / 10
Video Score: 10.0 / 10
The course includes 16h 38m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

3 articles.
17 resources.
0 exercise.
0 test.

Table of contents

Description

Welcome to the Complete Deep Learning Course 2021 With 7+ Real Projects

This course will guide you through how to use Google’s TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google’s TensorFlow framework in a way that is easy to understand. Other courses and tutorials have tended to stay away from pure tensorflow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning!
This course is designed to balance theory and practical implementation, with complete google colab and Jupiter notebook guides of code and easy to reference slides and notes. We also have plenty of exercises to test your new skills along the way!
This course covers a variety of topics, including
•Deep Learning.
•Google Colab
•Anaconda
•Jupiter Notebook
•Activation Function.
•Keras.
•Pandas.
•Seaborn.
•Feature scaling.
•Matplotlib.
•scikit-learn
•Sigmoid Function.
•Tanh Function.
•ReLU Function.
•Leaky Relu Function.
•Exponential Linear Unit Function.
•Swish function.
•Corpora.
•NLTK.
•TensorFlow 2.0
•Tokenization.
•Spacy.
•PoS tagging.
•NER.
•Stemming and lemmatization.
•Semantics and topic modelling.
•Sentiment analysis techniques.
•Lexicon-based methods.
•Rule-based methods.
•Statistical methods.
•Machine learning methods.
•Bernoulli RBMs.
•Introduction to RBMs (Restricted Boltzman Machine).
•Introduction to BMs (Boltzman Machine).
•Learning data representations with RBMs.
•Multilayer neural networks.
•Latent vector.
•Loading data.
•Analysing data.
•Training model.
•Compiling model.
•Visualizing data and model.
•Implementing multilayer neural networks
•Improving the model performance by removing outliers.
•Building a Keras deep neural network model
•Neural Network Basics.
•TensorFlow Basics.
•Artificial Neural Networks (ANN).
•Densely Connected Networks.
•Convolutional Neural Networks (CNN).
•Recurrent Neural Networks (RNN).
•AutoEncoders.
•Generative Adversarial Network (GAN).
•Deep Convolutional Generative adversarial network (DCGAN).
•Natural Language Processing (NLP).
•Image Processing.
•Sentiment Analysis.
•Restricted Boltzman Machine.
•Reinforcement Learning.
There are many Deep Learning Frameworks out there, so why use TensorFlow?
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are five big projects on healthcare problems and one small project to practice. These projects are listed below:
•Concrete Quality Prediction Using Deep Neural Networks.
•CIFAR-10.
•Classifying clothing images.
•20 newsgroups.
•Handwritten Digit.
•Denoising autoencoders (DAEs).
•Movie Reviews Sentiment Analysis Using Recurrent Neural Networks.
•Predicting Stock Price
•Iris Flower.

Become a machine learning, and deep learning guru today! We’ll see you inside the course!

Requirements

• There will be no Prerequisites.Basic knowledge of Python will be good.But everything will be taught from the round up.

You will learn

✓ Artificial Neural Networks (ANN)
✓ Convolution Neural Network (CNN)
✓ Recurrent Neural Network (RNN)
✓ Generative adversarial network (GAN)
✓ Deep Convolutional Generative adversarial network (DCGAN)
✓ Natural Language Processing (NLP)
✓ Image Processing
✓ Sentiment Analysis
✓ Autoencoder
✓ Restricted Boltzman Machine
✓ Deep Reinforcement Learning – Monte Carlo

This course is for

• Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence
• Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
• Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence.
• Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
• Any students in college who want to start a career in Data Science
• Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
• Any people who are not satisfied with their job and who want to become a Data Scientist.
• Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.
• AI experts who want to expand on the field of applications
• Data Scientists who want to take their AI Skills to the next level
• Students in tech-related programs who want to pursue a career in Data Science, Machine Learning, or Artificial Intelligence
• Anyone passionate about Artificial Intelligence

How much does the The Complete Deep Learning Course 2021 With 7+ Real Projects course cost? Is it worth it?

The course costs $11.99. And currently there is a 76% discount on the original price of the course, which was $49.99. So you save $38 if you enroll the course now.

Does the The Complete Deep Learning Course 2021 With 7+ Real Projects course have a money back guarantee or refund policy?

YES, The Complete Deep Learning Course 2021 With 7+ Real Projects has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the The Complete Deep Learning Course 2021 With 7+ Real Projects course, but there is a $38 discount from the original price ($49.99). So the current price is just $11.99.

Who is the instructor? Is Hoang Quy La a SCAM or a TRUSTED instructor?

Hoang Quy La has created 6 courses that got 42 reviews which are generally positive. Hoang Quy La has taught 2,224 students and received a 4.1 average review out of 42 reviews. Depending on the information available, Hoang Quy La is a TRUSTED instructor.

More info about the instructor, Hoang Quy La

Electrical Engineer
My name is Hoang Quy La. I did graduate from RMIT University as a first class honours in electrical engineering and I am currently studying master of software engineering in CDU at Australia. I have taught over 1250 students with 5 star reviews. I did develop a AI Chatbot with Tensorflow 2.0 with Flask by using Python and this Chatbot was implemented in the top University in Viet Nam. My current project is about AI in Healthcare applications. I also did complete my internship at SGS and Power System Company. Check my LinkedIn for all projects which I did in AI field.

10.0

CourseMarks Score®

9.9

Freshness

9.5

Feedback

10.0

Content

Platform: Udemy
Price: $11.99
Video: 16h 38m
Language: English
Next start: On Demand

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