Artificial Intelligence #5: MLP Networks with Scikit & Keras (Udemy.com)
Learn how to create Multilayer Perceptron Neural Network by using Scikit learn and Keras Libraries and Python
Created by: Sobhan N.
Produced in 2021
What you will learn
- Learn how Neural Networks work.
- Learn how Gradient Descent trained a neural network.
- Program Multilayer Perceptron Network from scratch in python.
- Predict output of model easily and precisely.
- Make program that able detect Bus and car.
- Learn how to use MLPClassifier for their purposes.
- Basic commands of Keras library to create Multilayer Perceptron Network.
- Use power of neural networks to forecast temperature of Los Angeles.
- Make forecasting model to estimate total airline passengers.
Quality Score
Overall Score : 100 / 100
Course Description
For example, in image recognition, they might learn to identify images that contain cats by analyzing example images that have been manually labeled as "cat" or "no cat" and using the results to identify cats in other images. They do this without any prior knowledge about cats, e.g., that they have fur, tails, whiskers and cat-like faces. Instead, they automatically generate identifying characteristics from the learning material that they process.
An ANN is based on a collection of connected units or nodes called artificial neurons which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it.
In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called 'edges'. Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer), to the last layer (the output layer), possibly after traversing the layers multiple times.
The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. ANNs have been used on a variety of tasks, including computer vision, speech recognition, machine translation, playing board and video games and medical diagnosis.
In this Course you learn multilayer perceptron (MLP) neural network by using Scikit learn & Keras libraries and Python.You learn how to classify datasets by MLP Classifier to find the correct classes for them. Next you go further. You will learn how to forecast time series model by using neural network in Keras environment.
In the first section you learn how to use python and sklearn MLPclassifier to forecast output of different datasets.
- Logic Gates
- Vehicles Datasets
- Generated Datasets
- Random datasets
- Forecast International Airline passengers
- Los Angeles temperature forecasting
Important information before you enroll:
- In case you find the course useless for your career, don't forget you are covered by a 30 day money back guarantee, full refund, no questions asked!
- Once enrolled, you have unlimited, lifetime access to the course!
- You will have instant and free access to any updates I'll add to the course.
- You will give you my full support regarding any issues or suggestions related to the course.
- Check out the curriculum and FREE PREVIEW lectures for a quick insight.
It's time to take Action!
Click the "Take This Course" button at the top right now!
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I can't wait to see you in the course!
Best Regrads,
Sobhan
Who this course is for:
- Anyone who wants to make the right choice when starting to learn Multilayer Perceptron Neural Network
- Anyone who wants to learn Keras
- Learners who want to work in data science and big data field
- students who want to learn machine learning
- Data analyser, Researcher, Engineers and Post Graduate Students need accurate and fast regression method.
- Modelers, Statisticians, Analysts and Analytic Professional.
Instructor Details
- 5.0 Rating
6 Reviews
Sobhan N.
My passion is teaching people through online courses. I love learning new skills, and since 2015 have been teaching people like you everything. I create courses that teach you how to become the better version of yourself with all kinds of skills.
What would you like to learn?
Would you like to learn Artificial Intelligence in python?
Would you like to make money creating landing pages?
Would you like to build your own AI programs & do something awesome for you?
Would you like to learn Xamarin to make both iOS/Android apps?
Would you like to learn how to write codes in HTML5 and CSS3?
Would you like to learn MATLAB the scientific language for researchers?
If you want to do any of these things, just enroll in the course. You have a 30-day money back guarantee if you don't like it. And I'm always improving my courses so that they stay up to date and the best that they can be. Check them out, and enroll today!
__________________________________________________________________________
About Sobhan N:
I have PhD degree in Electrical Engineering and like to learn anything about Electronics, Programming and Artificial Intelligence. I like electronic stuff like Arduino, Raspberry Pi and microcontrollers.
My passion is
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