PPT TENSORFLOW about and introduction and its working

about tensorflow

1. WELCOME TO TENSORFLOW SOFTWARE

2. TENSORFLOW TENSORFLOW IS A PYTHON-FRIENDLY OPEN SOURCE LIBRARY FOR NUMERICAL COMPUTATION THAT MAKES MACHINE LEARNING AND DEVELOPING NEURAL NETWORKS FASTER AND EASIER.   Google’s TensorFlow that ease the process of  Acquiring data Training models Serving predictions And refining future results

3. How TensorFlow works Tensorflow allows developers to create  dataflow graphs — Structures that describe how data moves through a  graph , A series of processing nodes. Each node in the graph represents a mathematical operation Each connection or edge between nodes is a multidimensional data array, or  tensor .

4. Real Time Applications Tensorflow :   the most famous deep learning library in the world is Google’s TensorFlow. Google product uses machine learning in all of its products to improve the search engine, translation, image captioning or recommendations. TensorFlow Example To give a concrete example, Google users can experience a faster and more refined search experience with AI. If the user types a keyword in the search bar, Google provides a recommendation about what could be the next word.

5. 1. Image Recognition It’s one of the most popular Uses of TensorFlow. It is used by Mobile companies, social media, and other telecom houses. Image recognition consists of pixel and pattern matching to identify the image and its parts. Image recognition consists of the following steps: a. Find out the features of pixel– Each image is a container of pixels which in turn are the combination of numbers. These numbers represent the color depth. b. Equip an image for training– Categorize the images under a different section to train a model. For example, classify an image as ‘car’, ‘bike’ etc for better understanding. For better performance, train a model using many images. c. Train the model to categorize images– With the help of various images, train a network that can produce a label as an output from the given image as an input. d. Provide an unknown input– Test the model by providing it a new image that can have a classification in any of the set categories. Image recognition finds its application in many domains including health care systems, banking systems, educational institutions, etc.

6. 2.Video Detection With increased technology, companies and businesses look forward to more secure and optimized systems. Hence, the motion detection is used widely at airport security checks, gaming controls, and movement detection. Here uses of TensorFlow include self-driving car systems, automation, and many automotive machines. To build a video detection environment, it follows the following steps: Setup the environment Provide the metadata and pictures Train the model Modify it to TensorFlow Lite Test the model It defines these highly advanced systems using the Object Detection API which takes the support of TensorFlow.

7. 3.Text-based applications The text messages, reactions, comments, tweets, stock results etc are a means of data. This processing of data is done using TensorFlow for the analysis purpose and reaching the expected sales. We do it using different techniques like sentiment analysis, a bag of words and many more. This can help to find out the risk associated with any organization by decoding the words used in texts. Furthermore, Google uses it for translating texts from one language to over 100 languages.

8. Summary Being an Open-Source library for deep learning and machine learning, there are many uses of TensorFlow. It finds a role to play in text-based applications, image recognition, voice search, and many more. It also finds its use in reinforcement learning which allows it to perform goal-oriented tasks such as robot navigation and reaching the winning criteria in video games. DeepFace, Facebook’s image recognition system uses TensorFlow for image recognition. Several real-world applications of deep learning make TensorFlow popular.

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