[ FreeCourseWeb ] Tensorflow with Python - Udemy torrent

Tensorflow with Python - Udemy

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 496 MB | Duration: 1h 29m
Learn practical use of TensorFlow and get skills on Data Analysis, TensorFlow, Deep Learning Application
What you'll learn
Learn installation of TensorFlow, Introduction of TensorFlow, different data types in TensorFlow, PyCharm IDE environment setup, etc
The set of skills that can be acquired upon completion of this TensorFlow training are Data Analysis, TensorFlow, Deep Learning Application
There are few skills also which could be obtained in completing this course are such as TensorFlow Model, Neural Networks, PyCharm IDE, TensorFlow Eager API, Linear regression, Logistic regression, and

Description
The TensorFlow is an open-source library for machine learning and deep learning applications. It is a freeware and does not require a license. TensorFlow was developed by Google Brain Team. TensorFlow was initially released in the year 2015. It was purely written in Python, C++ and CUDA languages. It supports multiple cross platforms such as macOS, Windows, Linux, Android, etc. It is mainly used in the form of a Math library. It was licensed under Apache License 2.0. The usage of Machine Learning contains the classification of basic elements and text, overfitting and underfitting, saving and restoration models. The production scale levels of Machine Learning include linear model, wide and deep learning, boosted trees, estimators based on CNN. The different generative models under TensorFlow are the translation, image captioning, DCGAN and VAE techniques. The different data representation ways in TensorFlow are a vector representation of words, kernel methods, large scale linear models and Unicode.

This TensorFlow is a machine learning platform that is under open source licensing. TensorFlow library can be used for both production and research applications. The different applications that can be carried out under TensorFlow are Research and experimentation, production scale Machine Learning, generative models, Images, Sequences, Load data, data representation, Non-Machine Learning applications.

The training will include the following:

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