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“…Work with image, text and video datasets to delve into real-world tasks Build apps for Android and iOS using Caffe, Core ML and Tensorflow Lite Book Description Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. …”

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Tabla de Contenidos: “…7.3.4 Class SportsUpdater -- 7.3.5 Class UserHandler -- 7.3.6 Class SportsClient -- 7.3.7 Class MatchFrame -- 7.4 Running -- 7.5 How to make this sample a real-world application -- Chapter 8. The sports team multiplexer sample -- 8.1 Introduction to the TeamMux sample -- 8.2 Classes in the TeamMux sample -- 8.2.1 Team -- 8.2.2 Match -- 8.2.3 TeamMuxSA -- 8.2.4 TeamClient -- 8.3 Step 1: Performing a light login -- 8.3.1 TeamMuxSA in step 1 -- 8.3.2 TeamClient in step 1 -- 8.4 Step 2: Logging in by token -- 8.4.1 TeamMuxSA in step 2 -- 8.4.2 TeamClient in step 2 -- 8.5 Step 3: Adding dynamic updates -- 8.5.1 Match and MatchListener -- 8.5.2 TeamMuxSA in step 3 -- 8.5.3 TeamClient in step 3 -- 8.6 Step 4 - Adding instant messaging support -- 8.6.1 TeamClient in step 4 -- Chapter 9. …”

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Tabla de Contenidos: “…-- Blockchain for Education: A New Credentialing Ecosystem -- Understanding blockchain technology -- Benef its of blockchain for educational credentialing -- Real-World implementations -- Driving change -- Conclusion -- Authors -- Figures -- Figure 1.1 Digitalisation at the Luwan No 1 Central Primary School in Shanghai -- Figure 1.2 The "digital classroom" system at Tongji University's first demonstration high school -- Figure 3.1 Six levels of automation towards the self-driving car -- Figure 3.2 Six levels of automation of personalised learning -- Figure 3.3 Three challenges for high-performance education with AI -- Figure 3.4 Multimodal data source to track learners and their environment -- Figure 3.5 Three types of interventions in domain independent actions -- Figure 3.6 Problems and dashboards in Snappet -- Figure 3.7 Problems and dashboards in MATHia -- Figure 3.8 Personalised remedial activities to learn decimals based on error patterns -- Figure 3.9 The Moment-by-Moment Learning Algorithm…”

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