TENSORFLOWPART 2

SOUBHI HADRI

COMPANIES USING TENSORFLOW

• GOOGLE • OPENAI • DEEPMIND • SNAPCHAT • UBER • AIRBUS • EBAY • DROPBOX • A BUNCH OF STARTUPS

SOME COOL PROJECTS USING TENSORFLOW

SOME COOL PROJECTS USING TENSORFLOW

SOME COOL PROJECTS USING TENSORFLOW

COLORNET

SOME COOL PROJECTS USING TENSORFLOWFor More visit Awesome Tensorflow

A curated list of awesome TensorFlow experiments, libraries, and projects. Inspired by awesome-machine-learning.

Tutorials, Libraries, Videos, PapersBlog posts, Community, BooksModels/Projects Powered by TensorFlow

https://github.com/jtoy/awesome-tensorflow

EXAMPLE 1: MINST.

• EACH IMAGE IS A 28X28 ARRAY, FLATTENED OUT TO BE A 1-D TENSOR OF SIZE 784

EXAMPLE 1: MINST.

• STEP 1: PROCESS DATA

EXAMPLE 1: MINST.

• STEP 2: CREATE PLACEHOLDERS FOR INPUTS AND LABELS

EXAMPLE 1: MINST.

• STEP 3: CREATE WEIGHT AND BIAS

EXAMPLE 1: MINST.

• STEP 4: BUILD MODEL TO PREDICT Y

EXAMPLE 1: MINST.

• STEP 5: SPECIFY LOSS FUNCTION

EXAMPLE 1: MINST.

• STEP 6: CREATE OPTIMIZER

EXAMPLE 1: MINST.

• STEP 7 : TRAIN OUR MODEL

EXAMPLE 1: MINST.

• TEST ACCURACY : 0.9172.

NOT ENOUGH GOOD!

EXAMPLE 1: MINST.USIGN CNN

• FIRST:CON->POOL

EXAMPLE 1: MINST.USIGN CNN

• SECOND:CON2->POOL2

EXAMPLE 1: MINST.USIGN CNN

• THIRD:FULL CONNECTED

EXAMPLE 1: MINST.USIGN CNN

• FOURTH:DROPOUT->FC2

EXAMPLE 1: MINST.USIGN CNN

• FINALLY:ADAM OPTIMIZER.

• 50 BATCH SIZE

• TEST ACCURACY : 0.9927.

HOW DOES TENSORFLOW KNOW WHAT VARIABLES TO UPDATE?

Session looks at all trainable variables that loss depends on and update them OR you can use the argument var_list (Optional list of Variable objects to update to minimize loss).

VISUALIZE IT WITH TENSORBOARD:

IN GOOGLE’S OWN WORDS: “THE COMPUTATIONS YOU'LL USE TENSORFLOW FOR - LIKE TRAINING A MASSIVE DEEP NEURAL NETWORK - CAN BE COMPLEX AND CONFUSING. TO MAKE IT EASIER TO UNDERSTAND, DEBUG, AND OPTIMIZE TENSORFLOW PROGRAMS, WE'VE INCLUDED A SUITE OF VISUALIZATION TOOLS CALLED TENSORBOARD.”

VISUALIZE IT WITH TENSORBOARD:

VISUALIZE IT WITH TENSORBOARD:

• WHEN A USER PERFORM CERTAIN OPERATIONS IN A TENSORBOARD-ACTIVATED TENSORFLOW PROGRAM, THESE OPERATIONS ARE EXPORTED TO AN EVENT FILE. TENSORBOARD IS ABLE TO CONVERT THESE EVENT FILES TO GRAPHS THAT CAN GIVE INSIGHT INTO A MODEL’S BEHAVIOR. LEARNING TO USE TENSORBOARD EARLY AND OFTEN WILL MAKE WORKING WITH TENSORFLOW THAT MUCH MORE ENJOYABLE AND PRODUCTIVE.

HTTPS://WWW.TENSORFLOW.ORG/API_GUIDES/PYTHON/SUMMARY

VISUALIZE IT WITH TENSORBOARD:

• EXAMPLE-CODECREATE A FILEWRITER OBJECT TO WRITE YOUR GRAPH TO EVENT FILES.

• TERMINAL

• BROWSER

• LEARN TO USE TENSORBOARD WELL AND OFTEN. IT WILL HELP A LOT WHEN YOU BUILD COMPLICATED MODELS.

VISUALIZE IT WITH TENSORBOARD:

• EXPLICITLY NAME THE VARIABLES

• TERMINAL

• BROWSER

• LEARN TO USE TENSORBOARD WELL AND OFTEN. IT WILL HELP A LOT WHEN YOU BUILD COMPLICATED MODELS.

MINST WITH CNN GRAPH

NOTES:

• BEWARE WHEN USING NUMPY ARRAYS BECAUSE NUMPY AND TENSORFLOW MIGHT BECOME NOT SO COMPATIBLE IN THE FUTURE!

• CONSTANTS ARE STORED IN THE GRAPH DEFINITION. THIS MAKES LOADING GRAPHS EXPENSIVE WHEN CONSTANTS ARE BIG. ONLY USE CONSTANTS FOR PRIMITIVE TYPES. USE VARIABLES OR READERS FOR MORE DAT

• EACH SESSION MAINTAINS ITS OWN COPY OF VARIABLE A THAT REQUIRES MORE MEMORY. SO TRY NOT TO OPEN MORE THAN ONE SESSION IN THE SAME TIME!

• LEARN TO USE TENSORBOARD WELL AND OFTEN. IT WILL HELP A LOT WHEN YOU BUILD COMPLICATED MODELS.

WHY TENSORFLOW

• TENSORFLOW COMMUNITY APPEARS TO MOVE VERY FAST. THE COMMUNITY IS STRANGELY ACTIVE.

• TENSORBOARD, CREATING A POWERFUL SET OF VISUALIZATIONS FOR BOTH NETWORK TOPOLOGY AND PERFORMANCE.

• TENSORFLOW OPERATES EASILY WITH MULTIPLE GPUS.

AWESOME NN DEMO USING TESNSORFLOW

• HTTP://PLAYGROUND.TENSORFLOW.ORG/

RESOURCES:

• OFFICIAL WEBSITE : HTTPS://WWW.TENSORFLOW.ORG• STANFORD CS 20SI.