1 00:00:08,809 --> 00:00:13,500 Every business wants to work smarter, and to do that you need to tap into your 2 00:00:13,500 --> 00:00:18,300 company's greatest resource, your data. But extracting the full value out of 3 00:00:18,300 --> 00:00:23,400 your data isn't always an easy process. First. you end up juggling an incredibly 4 00:00:23,400 --> 00:00:27,210 large and complex collection of tools that are used for finding and cleaning 5 00:00:27,210 --> 00:00:31,830 data, analyzing and generating visualizations of that data, and using 6 00:00:31,830 --> 00:00:36,030 the data to build and deploy machine learning models. And to make matters 7 00:00:36,030 --> 00:00:40,500 worse these tools are often a time drain to individually manage, and can be 8 00:00:40,500 --> 00:00:45,289 difficult to integrate into your system, which can really slow down the workflow. 9 00:00:45,289 --> 00:00:49,739 But not anymore. Using Watson Studio you can simplify 10 00:00:49,739 --> 00:00:54,000 your data projects with a streamlined process, that allows you to extract value 11 00:00:54,000 --> 00:00:59,219 and insights from your data to help your business get smarter, faster. It delivers 12 00:00:59,219 --> 00:01:02,820 an easy-to-use collaborative data science and machine learning environment 13 00:01:02,820 --> 00:01:07,380 for building and training models, preparing and analyzing data, and sharing 14 00:01:07,380 --> 00:01:12,390 insights, all in one place. Watson Studios easy to create 15 00:01:12,390 --> 00:01:16,380 visualizations and drag-and-drop code put the power of database 16 00:01:16,380 --> 00:01:20,789 decision-making into the hands of any member of your organization with no need 17 00:01:20,789 --> 00:01:25,830 for IT assistance. And if you need access to open source tools, the environment 18 00:01:25,830 --> 00:01:29,970 offers some of the most popular and powerful ones available. Watson Studio 19 00:01:29,970 --> 00:01:34,020 single environment also creates a workflow that's incredibly efficient so 20 00:01:34,020 --> 00:01:38,009 data scientists can share assets and work to solve problems within the system 21 00:01:38,009 --> 00:01:42,750 rather than starting from scratch every time a new issue arises. And developers 22 00:01:42,750 --> 00:01:46,590 can use that efficiency to quickly dive into building machine learning and deep 23 00:01:46,590 --> 00:01:50,280 learning algorithms. In fact, in the area of deep learning, 24 00:01:50,280 --> 00:01:54,569 Watson Studio supports some of the most popular frameworks and can deploy that 25 00:01:54,569 --> 00:01:58,979 deep learning on to the latest GPUs to help accelerate modeling by making it 26 00:01:58,979 --> 00:02:03,569 easier to use. The environments built-in neural network modeler also helps you 27 00:02:03,569 --> 00:02:07,470 build models with a simplified graphical interface even if you don't have the 28 00:02:07,470 --> 00:02:11,520 dedicated resources to build a model from scratch, Watson's Studio can help 29 00:02:11,520 --> 00:02:15,230 you get started with modeling templates for areas such as visual recognition, 30 00:02:15,230 --> 00:02:19,990 language classification, and other tools from IBM Watson services. 31 00:02:19,990 --> 00:02:24,440 Because Watson Studio is seamlessly integrated with the IBM Watson Knowledge 32 00:02:24,440 --> 00:02:29,030 Catalog, an intelligent asset discovery tool, you can transform data and models 33 00:02:29,030 --> 00:02:33,260 into trusted enterprise resources and collaborate with confidence, without 34 00:02:33,260 --> 00:02:39,530 compromising compliance, security or access control. Watson Studio provides 35 00:02:39,530 --> 00:02:44,720 many benefits for organizations helping to infuse AI into the business and drive 36 00:02:44,720 --> 00:02:50,690 innovation. You can train Watson Studio with embedded AI services including 37 00:02:50,690 --> 00:02:55,040 watson visual recognition. You can customize your models and deploy them as 38 00:02:55,040 --> 00:03:01,520 APIs or Core ML by using open source tools like Jupyter, Notebook, Anaconda 39 00:03:01,520 --> 00:03:06,980 and RStudio. Watson Studio supports most popular code libraries as well as 40 00:03:06,980 --> 00:03:11,989 no code visual modeling with neural network modeler for designing neural 41 00:03:11,989 --> 00:03:16,820 architectures using the most popular deep learning frameworks. In Watson 42 00:03:16,820 --> 00:03:22,220 Studio you can interactively discover, cleanse, and transform your data using 43 00:03:22,220 --> 00:03:27,260 data refinery. It helps you understand the quality and distribution of your 44 00:03:27,260 --> 00:03:32,330 data with built-in charts and statistics, and provides visualized results through 45 00:03:32,330 --> 00:03:36,980 interactive dashboards. Watson Studio includes an intuitive drag-and-drop 46 00:03:36,980 --> 00:03:41,630 interface that enables a non programmer to speed up the bottle building process 47 00:03:41,630 --> 00:03:46,459 by visually selecting, configuring, designing and auto coding neural 48 00:03:46,459 --> 00:03:52,220 networks. From development and training to production and evaluation, Watson 49 00:03:52,220 --> 00:03:56,989 Studio tracks your models over time to ensure you have the best performance for 50 00:03:56,989 --> 00:04:01,670 any given task using the best solutions across the entire lifecycle of your 51 00:04:01,670 --> 00:04:05,840 machine learning models.