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Getting Started with Orange 16: Text Preprocessing
 
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How to work with text in Orange, perform text preprocessing and create your own custom stopword list. For more information on text preprocessing, read the blog: [Text Preprocessing] https://blog.biolab.si/2017/06/19/text-preprocessing/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: https://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 19028 Orange Data Mining
Getting Started with Orange 17: Text Clustering
 
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How to transform text into numerical representation (vectors) and how to find interesting groups of documents using hierarchical clustering. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: https://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 16721 Orange Data Mining
Twitter Text Mining with Orange 3
 
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A simple example in using Orange 3 to mining texts from Twitter. Notice that collecting data and processing tweet profiles may take 1 minute or more for 500 corpus(es). This video also recorded common mistake in using Twitter widget which is not disabling "Collect result" option if you want a fresh dataset.
text mining 1
 
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In this video, we are going to start learning about text mining widgets in Orange3. In the following link you can find how to make Twitter API: https://developer.twitter.com/en/docs/ads/general/guides/getting-started
Views: 340 DataWiz
Classification in Orange (CS2401)
 
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A quick tutorial on analysing data in Orange using Classification.
Views: 44306 haikel5
Getting Started with Orange 18: Text Classification
 
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How to visualize logistic regression model, build classification workflow for text and predict tale type of unclassified tales. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: https://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 16829 Orange Data Mining
Predictive Analytics using Orange Data Mining
 
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Data Mining Fruitful and Fun Open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox. Download Link: https://orange.biolab.si/download/
Views: 2539 Anurag P
Introduction/tutorial to visual programming in Orange (python-based) a Data Mining Tool
 
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Sumaiya Iqbal, Broad Institute of MIT and Hardvard & MGH is giving a overview of Orange a python-based Data Mining Tool. This tool is useful for individuals with and without programming background. Sumaiya gives examples for hierarchical clustering, PCA, prediction and text mining.
Views: 3154 Dennis Lal
Tutoriel Orange Data Mining
 
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Vous trouverez dans cette vidéo un ensemble de fonctionnalités disponible sur le logiciel Orange Data Mining. La vidéo comprend les méthodes suivantes : - ACP - CAH - Abres de décision - Visualisation interactive des données - Evaluation des modeles (courbes ROC, matrices de confusion)
Views: 1230 SISE LYON2
Getting Started With Orange 05: Hierarchical Clustering
 
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Explanation of distance measurement between data points and a simple use of hierarchical clustering in the Orange workflow. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 53679 Orange Data Mining
Getting Started with Orange 08: Add-ons
 
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Installing add-ons in Orange and using them in combination with other widgets. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 31178 Orange Data Mining
Text mining 2
 
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In this video, we are going to continue to use Text Mining widgets in Orange. In order to download the datasets please go to: https://github.com/RezaKatebi/Crash-course-in-Object-Oriented-Programming-with-Python
Views: 171 DataWiz
Getting Started with Orange 06: Making Predictions
 
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Making predictions with classification tree and logistic regression. Train data set: http://tinyurl.com/fruits-and-vegetables-train Test data set: http://tinyurl.com/test-fruits-and-vegetables License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 64717 Orange Data Mining
Getting Started with Orange 04: Loading Your Data
 
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Loading your data in Orange from Google sheets or Excel. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 61667 Orange Data Mining
Getting Started with Orange 19: How to Import Text Documents
 
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How to import your own text files, create corpus and define custom class values from scratch. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: https://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 12041 Orange Data Mining
Preprocessing Data using Orange Data Mining
 
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Orange is a component-based data mining and machine learning software suite, featuring a visual programming front-end for explorative data analysis and visualization, and Python bindings and libraries for scripting. It includes a set of components for data preprocessing, feature scoring and filtering, modeling, model evaluation, and exploration techniques. It is implemented in C++ and Python. Its graphical user interface builds upon the cross-platform Qt framework. Orange is distributed free under the GPL. It is maintained and developed at the Bioinformatics Laboratory of the Faculty of Computer and Information Science, University of Ljubljana, Slovenia.
Views: 13633 Andi Ariffin
Topic Detection with Text Mining
 
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Meet the authors of the e-book “From Words To Wisdom”, right here in this webinar on Tuesday May 15, 2018 at 6pm CEST. Displaying words on a scatter plot and analyzing how they relate is just one of the many analytics tasks you can cover with text processing and text mining in KNIME Analytics Platform. We’ve prepared a small taste of what text mining can do for you. Step by step, we’ll build a workflow for topic detection, including text reading, text cleaning, stemming, and visualization, till topic detection. We’ll also cover other useful things you can do with text mining in KNIME. For example, did you know that you can access PDF files or even EPUB Kindle files? Or remove stop words from a dictionary list? That you can stem words in a variety of languages? Or build a word cloud of your preferred politician’s talk? Did you know that you can use Latent Dirichlet Allocation for automatic topic detection? Join us to find out more! Material for this webinar has been extracted from the e-book “From Words to Wisdom” by Vincenzo Tursi and Rosaria Silipo: https://www.knime.com/knimepress/from-words-to-wisdom At the end of the webinar, the authors will be available for a Q&A session. Please submit your questions in advance to: [email protected] This webinar only requires basic knowledge of KNIME Analytics Platform which you can get in chapter one of the KNIME E-Learning Course: https://www.knime.com/knime-introductory-course
Views: 3784 KNIMETV
Tutorial Preprocessing Data Menggunakan Orange Data Mining
 
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Video ini dibuat untuk memenuhi tugas 2 matakuliah Data Mining (CNH4E3) Disusun Oleh kelompok 4: Ananda Abdillah (1302140046) Arkan Priya Anggana Hadna (1302144061) Danar Satrio Aji (1302140056) Laode Muhammad Ikhsan (1302140046) Zaenal Abidin (1302140141)
Views: 655 Ananda Abdill
Getting Started with Orange 03: Widgets and Channels
 
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Orange data mining widgets and communication channels. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 56819 Orange Data Mining
Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Training | Edureka
 
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** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics. The following topics covered in this video : 1. The Evolution of Human Language 2. What is Text Mining? 3. What is Natural Language Processing? 4. Applications of NLP 5. NLP Components and Demo Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------------------- Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ --------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 34916 edureka!
Getting Started with Orange 11: k-Means
 
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Explanation of k-means clustering, and silhouette score and the use of k-means on a real data in Orange. For more information read the blogs on: [Learning with Paint Data] http://blog.biolab.si/2015/07/10/learn-with-paint-data/ [Interactive k-Means] http://blog.biolab.si/2016/08/12/interactive-k-means/ [Silhouette Scoring] http://blog.biolab.si/2016/03/23/all-i-see-is-silhouette/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 24839 Orange Data Mining
Getting Started with Orange 01: Welcome to Orange
 
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Introduction to Orange data mining software. Learn about the development of Orange workflows, data loading, basic machine learning algorithms and interactive visualizations. Download Orange from: https://orange.biolab.si/download/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 174362 Orange Data Mining
Getting Started With Orange 09: Principal Component Analysis
 
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Dimensionality reduction with principal component analysis. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 28843 Orange Data Mining
R tutorial: Getting started with text mining?
 
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Learn more about text mining with R: https://www.datacamp.com/courses/intro-to-text-mining-bag-of-words Boom, we’re back! You used bag of words text mining to make the frequent words plot. You can tell you used bag of words and not semantic parsing because you didn’t make a plot with only proper nouns. The function didn’t care about word type. In this section we are going to build our first corpus from 1000 tweets mentioning coffee. A corpus is a collection of documents. In this case, you use read.csv to bring in the file and create coffee_tweets from the text column. coffee_tweets isn’t a corpus yet though. You have to specify it as your text source so the tm package can then change its class to corpus. There are many ways to specify the source or sources for your corpora. In this next section, you will build a corpus from both a vector and a data frame because they are both pretty common.
Views: 5186 DataCamp
Machine Learning With Orange
 
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For more videos Please visit my online training school at https://datasciencemastery.teachable.com/ Please contact [email protected] (91-9920613669) for machine learning trainings. I am based in Bangalore. I also teach at Respro Academy 154/11 radhakrishna Building, Opp IIM, Bannerghatta Main Rd, Panduranga Nagar, Bengaluru, Karnataka 560076
Views: 2722 Data Science Mastery
Machine Learning with Orange - Tutorial
 
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As a joke amongst friends, I made this video on Machine Learning using this amazing data mining tool known as Orange. It makes the process of understanding machine learning a lot easier. For more information check out : https://www.youtube.com/channel/UClKKWBe2SCAEyv7ZNGhIe4g
Views: 421 G C KEERTHI Vasan
Data Mining mit Orange
 
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Andreas Bresser https://2013.de.pycon.org/schedule/sessions/3/ Es wird eine einfache Einführung in das Thema Data Mining gegeben. Dazu werden anschauliche Beispiele für den Einsatz von Orange gezeigt. Orange ist ein Open Source Programm, das Data Mining und Datenvisualisierung durch visuelle Programmierung oder Python Scripting ermöglicht.
Views: 1571 Next Day Video
Orange Data Mining tool
 
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For more information visit orange.biolab.si
Views: 8471 Deeksha Acharya
Getting Started with Orange 15: Image Analytics - Classification
 
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How to use embeddings for image classification and what can misclassifications tell us. Images kindly provided by: The Bouq at https://bouqs.com/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: https://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 17996 Orange Data Mining
Spectral Orange: Introduction
 
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Introduction to Spectral Orange, a flavor of Orange for analyzing spectroscopy data. Please note that Collagen spectroscopy data set has been renamed to Liver spectroscopy. Full Quasar package: https://quasar.codes/ Get Orange: https://orange.biolab.si/ See Spectroscopy add-on: https://github.com/markotoplak/orange-infrared License: GNU GPL + CC Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana In collaboration with: Soleil Synchrotron, Elettra Sincrotrone Trieste, BioSpec Norway and Canadian Light Source. Design: Agnieszka Rovšnik Music: THE HAPPY SONG by Nicolai Heidlas Music https://soundcloud.com/nicolai-heidlas Creative Commons — Attribution 3.0 Unported— CC BY 3.0 http://creativecommons.org/licenses/b... Music promoted by Audio Library https://youtu.be/cGuaRsXLScQ
Views: 4833 Orange Data Mining
Getting Started with Orange 12: k-Means Explained
 
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Interactive explanation of k-means algorithm and how the algorithm can potentially fail. For more information on teaching or learning the k-means, read the blog: [Interactive k-Means] http://blog.biolab.si/2016/08/12/interactive-k-means/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 17975 Orange Data Mining
Getting Started with Orange 20: Multivariate Projection - Freeviz
 
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How to visualize multiple variables in Orange and what how to interpret the Freeviz projection. For more information read the blogs on: [Visualizing Multiple Variables with Freeviz] https://blog.biolab.si/2018/01/26/visualizing-multiple-variables-freeviz/ [Scatter Plot Projection Rank] https://blog.biolab.si/2015/08/28/scatter-plot-projection-rank/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 7532 Orange Data Mining
Data mining - Preprocess with Orange
 
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handle for missing value :)
Views: 124 Abdul Raffi
Getting Started with Orange 14: Image Analytics - Clustering
 
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How to work with images in Orange, what are image embeddings and how do perform clustering with embedded data. For more information on image clustering, read the blog: [Image Analytics: Clustering] https://blog.biolab.si/2017/04/03/image-analytics-clustering/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: https://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 18662 Orange Data Mining
Spectral Orange: Preprocess
 
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How to construct a preprocessing pipeline for spectroscopy in Orange and how to visually observe the effect of different preprocessing methods. Get Orange: https://orange.biolab.si/ See Spectroscopy add-on: https://github.com/Quasars/orange-spectroscopy License: GNU GPL + CC Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana In collaboration with: Soleil Synchrotron, Elettra Sincrotrone Trieste, BioSpec Norway and Canadian Light Source. Design: Agnieszka Rovšnik Music: THE HAPPY SONG by Nicolai Heidlas Music https://soundcloud.com/nicolai-heidlas Creative Commons — Attribution 3.0 Unported— CC BY 3.0 http://creativecommons.org/licenses/b... Music promoted by Audio Library https://youtu.be/cGuaRsXLScQ
Views: 1372 Orange Data Mining
Getting Started with Orange 07: Model Evaluation and Scoring
 
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Evaluating classifiers on iris data set and visualizing misclassifications. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 39435 Orange Data Mining
Getting Started with Orange 02: Data Workflows
 
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Creating a data analysis workflow in Orange data mining software. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 89102 Orange Data Mining
Getting Started with Orange 13: Silhouette
 
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Explanation of silhouette score and how to use it for finding the outliers and the inliers. For more information on silhouette score, read the blog: [Silhouette Score] http://blog.biolab.si/2016/03/23/all-i-see-is-silhouette/ License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 19205 Orange Data Mining
tutorial prepocessing using orange
 
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data mining
Views: 873 Moh Zidni Mubarok
Orange data mining
 
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Descripcion
Views: 8206 Hector Hurtarte
Data Mining (CSH4G3) - Preprocessing with Orange
 
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This video was made to accomplish our task in Telkom University, Data Mining class in Informatics Engineering. Anggit Magfirani Fadhilla Yasmine Azalia Indira Suri Azarine Mukuan Lorenzo Albert Ramadhyni Rifani SIDE-39-GAB01
Views: 26 Mukuan Lorenzo
Prepare your data for ML  | Text Classification Tutorial Pt. 1 (Coding TensorFlow)
 
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@lmoroney is back with another episode of Coding TensorFlow! In this episode, we discuss Text Classification, which assigns categories to text documents. This is part 1 of a 2 part sub series that focuses on the data and gets it ready to train a neural network. Laurence also explains the unique challenges associated with Text Classification. Watch to follow along and stay tuned for part 2 of this episode where we’ll look at how to design a neural network to accept the data we prepared. Hands on tutorial → http://bit.ly/2CNVMbi Watch Part 2 https://www.youtube.com/watch?v=vPrSca-YjFg Subscribe to TensorFlow → http://bit.ly/TensorFlow1 Watch more Coding TensorFlow → http://bit.ly/2zoZfvt
Views: 16625 TensorFlow