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(This article was first published on <strong><a href="http://r-posts.com/r-in-the-data-science-stack-at-odsc/"> R-posts.com</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p><a rel="nofollow" href="https://hubs.ly/H08vBkG0" target="_blank"><img data-orig-file="https://i2.wp.com/r-posts.com/wp-content/uploads/2017/08/white-board-stack-R.png?fit=711%2C400" data-orig-size="711,400" data-medium-file="https://i2.wp.com/r-posts.com/wp-content/uploads/2017/08/white-board-stack-R.png?fit=450%2C253" data-attachment-id="280" data-image-meta="{" data-image-description="" src="https://i2.wp.com/r-posts.com/wp-content/uploads/2017/08/white-board-stack-R.png?resize=450%2C253" data-permalink="http://r-posts.com/r-in-the-data-science-stack-at-odsc/white-board-stack-r/" data-large-file="https://i2.wp.com/r-posts.com/wp-content/uploads/2017/08/white-board-stack-R.png?fit=450%2C253" alt="" data-image-title="white-board-stack-R" sizes="(max-width: 450px) 100vw, 450px" data-comments-opened="1" class="wp-image-280" data-recalc-dims="1"></a><a rel="nofollow" href="https://hubs.ly/H08vzL90" target="_blank"></a></p>
<p><a rel="nofollow" href="https://hubs.ly/H08vBkG0" target="_blank"><br>
Register now</a> for ODSC West in San Francisco, November 2-4 and save 60% <b>with code RB60</b> until September 1st.</p>
<p>R continues to hold its own in the data science landscape thanks in no small part to its flexibility.  That flexibility allows R to integrate with some of the most popular data science tools available.</p>
<p>Given R’s memory bounds, it’s no surprise that deep learning tools like Tensorflow are on that list. Comprehensive, intuitive, and well documented, Tensorflow has quickly become one of the most popular deep learning platforms and RStudio released a package to integrate with the Tensorflow API. Not to be outdone MXNet, another popular and powerful deep learning framework has native support for R with an API interface.  </p>
<p>It doesn’t stop with deep learning. Data science is moving real-time and the streaming analytics platform, Apache Kafka, is rapidly gaining traction with the community.  The kafka package allows one to use the Kafka messaging queue via R. Spark is now one of the dominant machine learning platforms and thus we see multiple R integrations in the form of the spark package and the SparkR package. The list will continue to grow with package integrations released for H20.ai, Druid etc. and more on the way.</p>
<p>At the  <a rel="nofollow" href="https://hubs.ly/H08vBlz0" target="_blank">Open Data Science Conference</a>, R has long been one of the most popular data science languages and ODSC West 2017 is no exception. We have a strong lineup this year that includes:</p>
<ul>
<li>R Tools for Data Science</li>
<li>Modeling Big Data with R, sparklyr, and Apache Spark</li>
<li>Machine Learning with R</li>
<li>Introduction to Data Science with R</li>
<li>Modern Time-Series with Prophet</li>
<li>R4ML: A Scalable and Distributed framework in R for Machine Learning</li>
<li>Databases Using R</li>
<li>Geo-Spatial Data Visualization using R</li>
</ul>
<p>From an R user perspective, one of the most exciting things about ODSC West 2017 is that it offers an excellent opportunity to do a deep dive into some of the most popular data science tools you can now leverage with R. Talks and workshops on the <a rel="nofollow" href="https://hubs.ly/H08vz5Z0" target="_blank">conference schedule</a> include:</p>
<ul>
<li>Deep learning from Scratch WIth Tensorflow</li>
<li>Apache Kafka for Real-time analytics</li>
<li>Deep learning with MXNet</li>
<li>Effective TensorFlow</li>
<li>Building an Open Source Analytics Solution with Kafka and Druid</li>
<li>Deep Neural Networks with Keras</li>
<li>Robust Data Pipelines with Apache Airflow</li>
<li>Apache Superset – A Modern, Enterprise-Ready Business Intelligence Web Application</li>
</ul>
<p>Over 3 packed days, ODSC West 2017 also offers a great opportunity to brush up on your modeling skills that include predictive analytics, time series, NLP, machine learning, image recognition, deep learning. autonomous vehicles, and AI chatbot assistants. Here’s just a few of the <a rel="nofollow" href="https://hubs.ly/H08vzL90" target="_blank">data science workshops</a> and talks scheduled:</p>
<ul>
<li>Feature Selection from High Dimensions</li>
<li>Interpreting Predictions from Complex Models</li>
<li>Deep Learning for Recommender Systems</li>
<li>Natural Language Processing in Practice – Do’s and Don’ts</li>
<li>Machine Imaging recognition</li>
<li>Training a Prosocial Chatbot</li>
<li>Anomaly Detection Using Deep Learning</li>
<li>Myths of Data Science: Practical Issues You Can and Can Not Ignore.</li>
<li>Playing Detective with CNNs</li>
<li>Recommendation System Architecture and Algorithms</li>
<li>Driver and Occupants Monitoring AI for Autonomous Vehicles</li>
<li>Solving Impossible Problems by Collaborating with an AI</li>
<li>Dynamic Risk Networks: Mapping Risk in the Financial System</li>
</ul>
<p>With over 20 full training session, 50 workshops and 100 speakers, ODSC West 2017 is ideal for beginners to experts looking to understand the latest in R tools and topics in data science and AI.</p>
<p><a rel="nofollow" href="https://hubs.ly/H08vBkG0" target="_blank">Register now</a> and <strong>save 60% with code RB60</strong> until September 1st.</p>
<p><em><a rel="nofollow" href="https://www.linkedin.com/in/sheamus/" target="_blank">
<p>Sheamus McGovern, CEO of ODSC</p></a>
	<p>
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