課程介紹

*** As seen on Kickstarter ***

Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind’s

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哪些人適合這堂課？

• Anyone interested in Deep Learning
• Students who have at least high school knowledge in math and who want to start learning Deep Learning
• Any intermediate level people who know the basics of Machine Learning or Deep Learning, including the classical algorithms like linear regression or logistic regression and more advanced topics like Artificial Neural Networks, but who want to learn more about it and explore all the different fields of Deep Learning
• Anyone who is not that comfortable with coding but who is interested in Deep Learning and wants 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 Deep Learning
• 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 Deep Learning tools
• Any business owners who want to understand how to leverage the Exponential technology of Deep Learning in their business
• Any Entrepreneur who wants to create disruption in an industry using the most cutting edge Deep Learning algorithms

學習目標

• Understand the intuition behind Artificial Neural Networks
• Apply Artificial Neural Networks in practice
• Understand the intuition behind Convolutional Neural Networks
• Apply Convolutional Neural Networks in practice
• Understand the intuition behind Recurrent Neural Networks
• Apply Recurrent Neural Networks in practice
• Understand the intuition behind Self-Organizing Maps
• Apply Self-Organizing Maps in practice
• Understand the intuition behind Boltzmann Machines
• Apply Boltzmann Machines in practice
• Understand the intuition behind AutoEncoders
• Apply AutoEncoders in practice

課程介紹

You’re looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in Python, right?

You’ve found the right Neural Networks course!

After completing this course you will be abl

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哪些人適合這堂課？

• People pursuing a career in data science
• Working Professionals beginning their Neural Network journey
• Statisticians needing more practical experience
• Anyone curious to master ANN from Beginner level in short span of time

學習目標

• Get a solid understanding of Artificial Neural Networks (ANN) and Deep Learning
• Understand the business scenarios where Artificial Neural Networks (ANN) is applicable
• Building a Artificial Neural Networks (ANN) in Python
• Use Artificial Neural Networks (ANN) to make predictions
• Learn usage of Keras and Tensorflow libraries
• Use Pandas DataFrames to manipulate data and make statistical computations.

課程介紹

You’re looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in R, right?

You’ve found the right Neural Networks course!

After completing this course you will be able to:

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哪些人適合這堂課？

• People pursuing a career in data science
• Working Professionals beginning their Neural Network journey
• Statisticians needing more practical experience
• Anyone curious to master ANN from Beginner level in short span of time

學習目標

• Get a solid understanding of Artificial Neural Networks (ANN) and Deep Learning
• Understand the business scenarios where Artificial Neural Networks (ANN) is applicable
• Building a Artificial Neural Networks (ANN) in R
• Use Artificial Neural Networks (ANN) to make predictions
• Use R programming language to manipulate data and make statistical computations
• Learn usage of Keras and Tensorflow libraries

課程介紹

*** NOW IN TENSORFLOW 2 and PYTHON 3 ***

Learn about one of the most powerful Deep Learning architectures yet!

The Recurrent Neural Network (RNN) has been used to obtain state-of-the-art results in sequence modeling.

This includes time series anal

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哪些人適合這堂課？

• Students, professionals, and anyone else interested in Deep Learning, Time Series Forecasting, Sequence Data, or NLP
• Software Engineers and Data Scientists who want to level up their career

學習目標

• Apply RNNs to Time Series Forecasting (tackle the ubiquitous “Stock Prediction” problem)
• Apply RNNs to Natural Language Processing (NLP) and Text Classification (Spam Detection)
• Apply RNNs to Image Classification
• Understand the simple recurrent unit (Elman unit), GRU, and LSTM (long short-term memory unit)
• Write various recurrent networks in Tensorflow 2
• Understand how to mitigate the vanishing gradient problem

課程介紹

This course is about artificial neural networks. Artificial intelligence and machine learning are getting more and more popular nowadays. In the beginning, other techniques such as Support Vector Machines outperformed neural networks, but in the 21th

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哪些人適合這堂課？

• This course is recommended for students who are interested in artificial intelligence focusing on neural networks

學習目標

• Basics of neural networks
• Hopfield networks
• Concrete implementation of neural networks
• Backpropagation
• Optical character recognition

課程介紹

Machine learning is an extremely hot area in Artificial Intelligence and Data Science. There is no doubt that Neural Networks are the most well-regarded and widely used machine learning techniques.

A lot of Data Scientists use Neural Networks withou

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哪些人適合這堂課？

• Beginner data scientists interested in using Artificial Neural Networks and deep learning
• Expert data scientists interested in expanding their knowledge of how Neural Networks work internally
• Researchers who want to design and analyze current and new Neural Networks

學習目標

• The structure of Neural Networks
• The learning process of Neural Networks
• Visualization in Neural Networks
• Deep learning and deep Neural Networks
• How to do classification using Neural Networks
• How to do regression and prediction using Neural Networks
• Implementing Neural Networks in Java
• Using Neuroph to design, test, and analyze Neural Networks

課程介紹

Artificial neural networks are considered to be the most efficient Machine Learning techniques nowadays, with companies the likes of Google, IBM and Microsoft applying them in a myriad of ways. You’ve probably heard about self-driving cars or applica

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哪些人適合這堂課？

• Beginners who are starting to learn about Artificial Neural Networks or Deep Learning
• People interested in the theory of Artificial Neural Networks
• Undergraduate students who are studying subjects related to Artificial Intelligence
• Anyone interested in Artificial Intelligence or Artificial Neural Networks

學習目標

• Learn step by step all the mathematical calculations involving artificial neural networks
• Implement neural networks in Python and Numpy from scratch
• Understand concepts like perceptron, activation functions, backpropagation, gradient descent, learning rate, and others
• Build neural networks applied to classification and regression tasks
• Implement neural networks using libraries, such as: Pybrain, sklearn, TensorFlow, and PyTorch

課程介紹

YOUR COMPLETE GUIDE TO PRACTICAL NEURAL NETWORKS & DEEP LEARNING IN R:       

This course covers the main aspects of neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based dat

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哪些人適合這堂課？

• People Wanting To Master The R & R Studio Environment For Data Science
• Anyone With Prior Exposure To Common Machine Learning Concepts Such As Supervised Learning
• Students Wishing To Learn The Implementation Of Neural Networks On Real Data In R
• Students Wishing To Learn The Implementation Of Basic Deep Learning Concepts In R

學習目標

• Be Able To Harness The Power Of R For Practical Data Science
• Read In Data Into The R Environment From Different Sources & Carry Out Basic Pre-processing Tasks
• Master The Theory Of Artificial Neural Networks (ANN)
• Implement ANN For Classification & Regression Problems In R
• Implement Deep Learning In R
• Learn The Usage Of The Powerful H2o Package
• Learn The Implementation Of Both ANN & DNN Using The H2o Package Of R Programming Language

課程介紹

Let’s dive into data science with python and predict stock prices  and customer sentiment.

machine learning / ai ? How to learn machine learning in python? And what is transfer learning ? How to use it ? How to create a sentiment classification algo

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哪些人適合這堂課？

• It’s a hands on course so Your committment to code along with me
• beginners to intermediate students in neural networks and machine learning who already know the basics
• students who are eager to learn and dive into one of the hottest topics currently out there
• students who ask how to do stock market predictions with neural networks
• students who ask how to do sentiment analysis with neural networks

學習目標

• You can create an LSTM neural network and do a basic stock price prediction
• You know how to do sentiment analysis with LSTM neural networks
• You increase your knowledge and understanding of the deep learning library keras and pyhton
• You might open up new career opportunities for you which are not only highly rewarding but also offer more job satisfaction

課程介紹

From Google Translate to Netflix recommendations, neural networks are increasingly being used in our everyday lives. One day neural networks may operate self driving cars or even reach the level of artificial consciousness. As the machine learning re

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哪些人適合這堂課？

• Anyone interested in machine learning

學習目標

• Neural Networks
• Machine Learning
• Artificial Intelligence
• Supervised Learning