A-Z Course for Google's Deep Learning Framework - TensorFlow with Python! Learn to use functions and apply Codes.
This course will guide you through how to use Google’s TensorFlow framework to create artificial neural networks for deep learning and also the basics of Machine 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 and its application .
Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That’s just the average! And it’s not just about money - it’s interesting work too!
If you’ve got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This is a comprehensive course with very crisp and straight forward intent.
This course covers a variety of topics, including
- Neural Network Basics
- TensorFlow detailed,Keras,Sonnet etc
- Artificial Neural Networks
- Types of Neural network
- Feed forward network
- Radial basis network
- Kohonen Self organizing maps
- Recurrent neural Network
- Modular Neural networks
- Densely Connected Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Machine Learning
- Deep Learning Framework comparisons
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, IBM, Intel, and of course, Google!
Become a machine learning guru today! We’ll see you inside the course!
Who is the target audience?
- Anyone interested in Machine Learning,Deep Learning
- Students who have at least high school knowledge in math and who want to start learning Machine 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 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
☞ Deep Learning for Computer Vision with Tensor Flow and Keras
☞ Introduction to Machine Learning & Deep Learning in Python
☞ Tensorflow and Keras For Neural Networks and Deep Learning
☞ Build Neural Networks In Seconds Using Deep Learning Studio
☞ Deep Learning Project Building with Python and Keras
☞ Deep Learning & Neural Networks Python - Keras : For Dummies