Android has an inbuilt feature speech to text through which you can provide speech input to your app. With this feature you can add some of the cool features to your app like adding voice navigation and it is very helpful when you are targeting disabled people. In the background how voice input works is, the speech input will be streamed to a server, on the server voice will be converted to text and finally text will be sent back to our app. Other tutorials : 1) Create a custom AVD :https://youtu.be/Cg7BVTk6r5E 2) Basic Android App :http://youtu.be/q98NC73LEgI 3) Calculator App :https://youtu.be/mrjOLG2Grt0 4) How to create a new activity :https://youtu.be/-xljI2_TRZg 5) How to create a login form :https://youtu.be/x6jQAaLz1O8 Find me here : Tumblr : https://www.tumblr.com/blog/priyanka0304 Google+ : https://plus.google.com/u/0/b/105970252005982916681/105970252005982916681/posts Twitter : https://twitter.com/AndroidAcademy1 Facebook : https://www.facebook.com/AndroidAcademy8?ref=hl
In this keynote, we announced the launch of Databricks Machine Learning, the first enterprise ML solution that is data-native, collaborative, and supports the full ML lifecycle. This launch introduces a new purpose-built product surface Databricks ML provides a solution for the full ML lifecycle by supporting any data type at any scale, enabling users to train ML models with the ML framework of their choice and managing the model deployment lifecycle – from large scale batch scoring to low latency online serving. Additionally, we announced two machine learning capabilities. First, Databricks Feature Store, the first feature store codesigned with a data and MLOps platform. Second, Databricks AutoML, a ‘glass box’ approach to autoML that accelerates model development without sacrificing control and transparency. Finally, this keynote covers and end-to-end demo of Databricks Machine Learning. Register for free to see the rest of the keynotes and exciting announcements live, plus over 200+ sessions. Learn from the creators and top contributors of technologies like PyTorch, TensorFlow, MLflow, Delta Lake, Apache Spark, Hugging Face, DBT and more. https://databricks.com/dataaisummit/north-america-2021 Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc/
Hi. In this lecture will transform tokens into features. And the best way to do that is Bag of Words. Let’s count occurrences of a particular token in our text. The motivation is the following. We’re actually looking for marker words like excellent or disappointed, and we want to detect those words, and make decisions based on absence or presence of that particular word, and how it might work. Let’s take an example of three reviews like a good movie, not a good movie, did not like. Let’s take all the possible words or tokens that we have in our documents. And for each such token, let’s introduce a new feature or column that will correspond to that particular word. So, that is a pretty huge metrics of numbers, and how we translate our text into a vector in that metrics or row in that metrics. So, let’s take for example good movie review. We have the word good, which is present in our text. So we put one in the column that corresponds to that word, then comes word movie, and we put one in the second column just to show that that word is actually seen in our text. We don’t have any other words, so all the rest are zeroes. And that is a really long vector which is sparse in a sense that it has a lot of zeroes. And for not a good movie, it will have four ones, and all the rest of zeroes [More]
This video introduces us to the basics of deep learning as to how it is very effective for unstructured data as it does not need feature engineering to be done for images or audio or video or text. Instead it can help in automated feature extraction in form of a hierarchy of concepts which is automated which can further feed to classification or clustering or other machine learning problems. LinkedIn: https://www.linkedin.com/in/tarah-ai-8316b7153/ Twitter: https://twitter.com/tarahtech #AI #DeepLearning #ReinforcementLearning #MachineLearning #ML #DL #DataScience #ArtificialIntelligence #Classification #Jobs #Regression #Clustering #Intelligence #Learn #Intelligence #Knowledge #LearnFromHome #BI #BA #Analytics #Insights #Visualization #Graphs #Robots #Speech #BackPropagation #CNN #RNN #LSTM #NeuralNetworks #Network #Prediction #BigData #Hadoop #Spark #Python #LearnPython #LearnAI #LearnMachineLearning #LearnML #jobs #annotators #newjobs #employment #AI #ArtificialIntelligence #ML #automation #labeling #ethics #robotics #reskilling #AI #Automation #jobs #newskills #oldskills #reinvention #humanresources #deeplearning #featureextraction #featureengineering #Automatedfeaturextraction #hierarchy #NLP #ComputerVision #SpeechProcessing #UnstructuredData #AI
War Robots [3.4] Test Server Gameplay with the NEW Multi-Hanger Feature. so let me start a Rant , through the past 2 years i kept crying to Pixonic in order to give us the option to chose which map we want to play on in order to Avoid all those cancerous Long Range Weapons , they Told me “we don’t want people to play on specific maps with Specific Hangers and gain an Advantage” , at that point i was still unsatisfied because that issue can be fixed in many ways , but i didn’t complain further because their excuse was acceptable. well apparently that was all a lie in order to introduce this feature and force people into having twice (and up to 5 times) more maxed Robots and weapons if they want to play on any Map with the perfect hanger all the time , Pixonic never gave a shit about Balancing or fair Gameplay from the start , i was a dumbass to believe them. a similar story with the windows platform , they separated it from Android just to force people into starting new account and buy Premium and gold rather than keep playing on their already existing accounts with the excuse that “Windows and Android are incompatible with each other” , well that’s Stupid , there are many Cross-Platform Games out there and WR doesn’t have anything that prevents it from being like them , but the more accounts you have the more likely that [More]