Download: Deep Learning & Neural Networks Python – Keras : For Dummies by Abhilash Nelson
Deep Learning & Neural Networks Python – Keras : For Dummies is the course offered by udemy for all those who want to know more about this topic.
Deep Learning and Data Science using Python and Keras Library – Beginner to Professional – The Complete Guide
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The course professor Abhilash Nelson
The Deep Learning & Neural Networks Python – Keras : For Dummies course is taught by Abhilash Nelson. For those who do not know, this author is one of the best trained on this subject. He has lectured many times, taught at major institutes, and enjoys a high reputation from his colleagues.
Learn more about Abhilash Nelson:
I am a pioneering, talented and security-oriented Android/iOS Mobile and PHP/Python Web Developer Application Developer offering more than eight years’ overall IT experience which involves designing, implementing, integrating, testing and supporting impact-full web and mobile applications.
Description about Deep Learning & Neural Networks Python – Keras : For Dummies
Hi this is Abhilash Nelson and I am thrilled to introduce you to my new course Deep Learning and Neural Networks using Python: For Dummies The world has been revolving much around the terms “Machine Learning” and “Deep Learning” recently. With or without our knowledge every day we are using these technologies. Ranging from google suggestions, translations, ads, movie recommendations, friend suggestions, sales and customer experience so on and so forth. There are tons of other applications too. No wonder why “Deep Learning” and “Machine Learning along with Data Science” are the most sought after talent in the technology world now a days. But the problem is that, when you think about learning these technologies, a misconception that lots of maths, statistics, complex algorithms and formulas needs to be studied prior to that. Its just like someone tries to make you believe that, you should learn the working of an Internal Combustion engine before you learn how to drive a car. The fact is that, to drive a car, we just only need to know how to use the user friendly control pedals extending from engine like clutch, brake, accelerator, steering wheel etc. And with a bit of experience, you can easily drive a car. The basic know how about the internal working of the engine is of course an added advantage while driving a car, but its not mandatory. Just like that, in our deep learning course, we have a perfect balance between learning the basic concepts along the implementation of the built in Deep Learning Classes and functions from the Keras Library using the Python Programming Language. These classes, functions and APIs are just like the control pedals from the car engine, which we can use easily to build an efficient deep learning model. Lets now see how this course is organized and an overview about the list of topics included. We will be starting with few theory sessions in which we will see an overview about the Deep Learning and neural networks. The difference between deep learning and machine learning, the history of neural networks, the basic work-flow of deep learning, biological and artificial neurons and applications of neural networks. In the next session, we will try to answer the most popular , yet confusing question weather we have to choose Deep Learning or machine learning for an upcoming project involving Artificial intelligence. We will compare the scenarios and factors which help us to decide in between machine learning or deep learning. And then we will prepare the computer and install the python environment for doing our deep learning coding. We will install the anaconda platform, which a most popular python platform and also install the necessary dependencies to proceed with the course. Once we have our computer ready, we will learn the basics of python language which could help if you are new to python and get familiar with the basic syntax of python which will help with the projects in our course. We will cover the details about python assignments, flow control, functions, data structures etc. Later we will install the libraries for our projects like Theano, Tensorflow and Keras which are the best and most popular deep learning libraries. We will try a sample program with each libraries to make sure its working fine and also learn how to switch between them. Then we will have another theory session in which we will learn the concept of Multi-Layer perceptrons, which is the basic element of the deep learning neural network and then the terminology and the Major steps associated with Training a Neural Network. We will discuss those steps in details in this session. After all these exhaustive basics and concepts, we will now move on to creating real-world deep learning models. At first we will download and use the Pima Indians Onset of Diabetes Dataset, with the training data of Pima Indians and whether they had an onset of diabetes within five years. We will build a classification model with this an…
Score according to professionals: 4.6
