SAP AI ; Predictive Maintenance ; Inference / Predictions using Jupyter
SAP AI ; Predictive Maintenance ; Inference / Predictions using Jupyter : In this playlist by Tahir Hussain Babar (Bob), from the SAP HANA Academy, we use SAP Artificial Intelligence to build a Deep Learning model on Acoustical Sound for Predictive Maintenance with SAP AI Core. In this video, we look at Inference by using Jupyter to look at a source sound file with our trained model to examine if there any noise anomalies (by using our training model). Base64 conversion is demonstrated, and we also look at analysing Inference results and how the Endpoint URL works. We finish by testing if the outputted sound classification from our prediction is correct by decoding it from Base64. 00:00 - Intro01:05 - How to use a Deployed Model02:31 - Analyzing local sound files03:57 - Converting sounds to base64 in Jupyter06:09 - Preparing Model for Inference06:58 - Analyzing Inference result & Endpoint URLSAP AI in BTP ; https://sap.to/6057zcebR SAP AI GitHub ; https://github.com/SAP-samples/btp-ai-sustainability-bootcampPlease note: This video was originally published on the SAP HANA Academy YouTube Channel and therefore may contain references to SAP HANA Academy and YouTube. The tech world is always evolving and the SAP HANA Academy YouTube channel is set to close on December 31, 2023. At that time, references will no longer be valid and will gradually be removed when the videos are updated.Also, this video includes automatically generated captions and therefore might misrepresent the spoken content or display incorrect product names. *************************This video also appears in that playlists :https://www.youtube.com/playlist?list=PLZrcgS4bXgXoEyOazuiVrHvPYdAl_y6-Ghttps://www.youtube.com/playlist?list=PLZrcgS4bXgXoAGC9UFbfiyJTmz0B_Unk4https://www.youtube.com/playlist?list=PLZrcgS4bXgXqA6OjZOn_ZaRsLqBQhDzFV
SAP AI ; Predictive Maintenance ; Inference / Predictions using Jupyter : In this playlist by Tahir Hussain Babar (Bob), from the SAP HANA Academy, we use SAP Artificial Intelligence to build a Deep Learning model on Acoustical Sound for Predictive Maintenance with SAP AI Core. In this video, we look at Inference by using Jupyter to look at a source sound file with our trained model to examine if there any noise anomalies (by using our training model). Base64 conversion is demonstrated, and we also look at analysing Inference results and how the Endpoint URL works. We finish by testing if the outputted sound classification from our prediction is correct by decoding it from Base64. 00:00 – Intro01:05 – How to use a Deployed Model02:31 – Analyzing local sound files03:57 – Converting sounds to base64 in Jupyter06:09 – Preparing Model for Inference06:58 – Analyzing Inference result & Endpoint URLSAP AI in BTP ; https://sap.to/6057zcebR SAP AI GitHub ; https://github.com/SAP-samples/btp-ai-sustainability-bootcampPlease note: This video was originally published on the SAP HANA Academy YouTube Channel and therefore may contain references to SAP HANA Academy and YouTube. The tech world is always evolving and the SAP HANA Academy YouTube channel is set to close on December 31, 2023. At that time, references will no longer be valid and will gradually be removed when the videos are updated.Also, this video includes automatically generated captions and therefore might misrepresent the spoken content or display incorrect product names. *************************This video also appears in that playlists :https://www.youtube.com/playlist?list=PLZrcgS4bXgXoEyOazuiVrHvPYdAl_y6-Ghttps://www.youtube.com/playlist?list=PLZrcgS4bXgXoAGC9UFbfiyJTmz0B_Unk4https://www.youtube.com/playlist?list=PLZrcgS4bXgXqA6OjZOn_ZaRsLqBQhDzFV
