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Courses>Data Science>Tensorflow with Python
DevelopmentTensorflow with Python
Price:Paid
Length:1.5 hours
Content type:video
level:all levels
Updated:05 March 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Data Science>Tensorflow with Python
Tensorflow with Python
3.7 (14.1k)
1.5 hours
14075 students
What you will learn
1Learn installation of TensorFlow, Introduction of TensorFlow, different data types in TensorFlow, PyCharm IDE environment setup, etc
2The set of skills that can be acquired upon completion of this TensorFlow training are Data Analysis, TensorFlow, Deep Learning Application
3There 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 TensorFlow, etc
Target audiences
1The learners who are holding any Bachelor’s engineering in Computer Science or any technical areas can choose this TensorFlow training as a better option in getting expertise in Deep Learning technologies. All the learners who are keen in learning and obtaining knowledge on Deep Learning techniques or Data processing or Big data analytics or Hadoop frameworks can opt for this TensorFlow course.
2Software Developer, Research Scientist, Data Analyst, Business Analyst, Hadoop Developer, Researcher, SAS Programmer, R Programmer, Machine Learning Engineer, Machine Learning Developer, AI Expert, Chatbots Developer, AI ML Engineer, Python Developer, Python ML Engineer, Solution Architect, Machine Learning Scientist, etc. This course can opt also to pursue better career opportunities in the area of Machine Learning or Deep learning processes.
Requirements
1The TensorFlow training does not contain any prerequisites and can be preferred by any learner to master the basic concepts or knowledge on Machine Learning, Deep learning, data analytics tools, data processing techniques using PyCharm IDE, etc. All the learners who are interested to learn the TensorFlow concepts such as installation and setup of deep learning model using TensorFlow library and python programming etc. Data Analysis and Data Visualization techniques can also be carried out using different tools using the TensorFlow library which is explained in this course.
2Any previous knowledge or hands-on in the areas of Data Analytics or Big Data Development or Hadoop Development or data analytics tools is an added advantage in further learning the contents of the TensorFlow training.
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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:

1. Tensorflow Installation using Pip and Anaconda Navigator
2. TensorFlow Introduction
3. Environment set up in PyCharm IDE and running Sample Hello World Program
4. Data Types used in TensorFlow and their handling in Python
5. Implementing Linear model example, calculating loss value and reducing loss value using Optimizer and Train
6. Updating existing data element value using Feed Dictionary
7. Placeholder example and Usage and declaration of Constructor
8. Addition of 2 numbers and progammatically calculation of Random numbers

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Make the most out of your online education
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Careertail
Courses>Data Science>Tensorflow with Python
DevelopmentTensorflow with Python
Price:Paid
Length:1.5 hours
Content type:video
level:all levels
Updated:05 March 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Data Science>Tensorflow with Python
Tensorflow with Python
3.7 (14.1k)
1.5 hours
14075 students
What you will learn
1Learn installation of TensorFlow, Introduction of TensorFlow, different data types in TensorFlow, PyCharm IDE environment setup, etc
2The set of skills that can be acquired upon completion of this TensorFlow training are Data Analysis, TensorFlow, Deep Learning Application
3There 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 TensorFlow, etc
Target audiences
1The learners who are holding any Bachelor’s engineering in Computer Science or any technical areas can choose this TensorFlow training as a better option in getting expertise in Deep Learning technologies. All the learners who are keen in learning and obtaining knowledge on Deep Learning techniques or Data processing or Big data analytics or Hadoop frameworks can opt for this TensorFlow course.
2Software Developer, Research Scientist, Data Analyst, Business Analyst, Hadoop Developer, Researcher, SAS Programmer, R Programmer, Machine Learning Engineer, Machine Learning Developer, AI Expert, Chatbots Developer, AI ML Engineer, Python Developer, Python ML Engineer, Solution Architect, Machine Learning Scientist, etc. This course can opt also to pursue better career opportunities in the area of Machine Learning or Deep learning processes.
Requirements
1The TensorFlow training does not contain any prerequisites and can be preferred by any learner to master the basic concepts or knowledge on Machine Learning, Deep learning, data analytics tools, data processing techniques using PyCharm IDE, etc. All the learners who are interested to learn the TensorFlow concepts such as installation and setup of deep learning model using TensorFlow library and python programming etc. Data Analysis and Data Visualization techniques can also be carried out using different tools using the TensorFlow library which is explained in this course.
2Any previous knowledge or hands-on in the areas of Data Analytics or Big Data Development or Hadoop Development or data analytics tools is an added advantage in further learning the contents of the TensorFlow training.
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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:

1. Tensorflow Installation using Pip and Anaconda Navigator
2. TensorFlow Introduction
3. Environment set up in PyCharm IDE and running Sample Hello World Program
4. Data Types used in TensorFlow and their handling in Python
5. Implementing Linear model example, calculating loss value and reducing loss value using Optimizer and Train
6. Updating existing data element value using Feed Dictionary
7. Placeholder example and Usage and declaration of Constructor
8. Addition of 2 numbers and progammatically calculation of Random numbers

Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot