Machine Learning With TensorFlow The Practical Guide
Machine Learning; an application of AI which is known to provide any system the ability to learn without programming. It allows software to predict the outcome more accurately. Machine learning proces...
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- English
Course Description
Machine Learning; an application of AI which is known to provide any system the ability to learn without programming. It allows software to predict the outcome more accurately. Machine learning processes the input data or instructions to form a pattern by statistical analysis for making better decisions. It is so common today that most of us use it on the daily basis and don’t even notice it. Like...
Machine Learning; an application of AI which is known to provide any system the ability to learn without programming. It allows software to predict the outcome more accurately. Machine learning processes the input data or instructions to form a pattern by statistical analysis for making better decisions. It is so common today that most of us use it on the daily basis and don’t even notice it. Likewise, Tensorflow was recently launched by Google as an open source library which is widely used for high-performance computations as required in machine learning. Knowing this fact, we launched Machine Learning with Tensorflow detailing its every aspects. Why this course is important? From Facebook’s news feed to self-driving cars, machine learning is available everywhere making its knowledge important for every developer. Successfully, it has created its impact on almost every type of businesses. Meanwhile, Tensorflow has become a perfect tool for machine learning by not only performing high computations but also allowing users to build the dataflows. This course comprises numerous topics with the sole aim to understand Tensorflow and machine learning. What makes this course so valuable? This course gives an insight into the basics of Tensorflow covering topics like tensors, operators and variables. It is a good option to master machine learning, its types and various main algorithms including linear regression. Furthermore, this course also covers advanced machine learning like a neural network, convolution neural network and others. Here, you’ll also gain the practice by implementing it in a project on Deep Neural Network.
What you’ll learn
- 1. Fundamentals of Tensorflow and its installation on Windows, Mac and Linux
- 2. Basics of Tensorflow including tensors, operators, variables and others
- 3. Basics of Machine Learning and its types
- 4. Main algorithms and its implementation - Linear regression, logistic regression, KNN regression and others
- 5. Clustering and its approaches
- 6. Advanced Machine Learning- Neural Networks, Convolution Neural Network, Recurrent Neural Networks
- 7. A project on Deep Neural Networks
Curriculum
Frequently Asked Questions
This course includes
- Lectures 44
- Duration 6 Hour
- Language English
- Certificate No