I know the pandemic is keeping everyone at home, home working is becoming the new normal for many of us, and it is hard

Round-robin retros can help you and your team have vulnerable conversations—and this builds trust and connection. Brené Brown captures it perfectly in her book Daring Greatly:

http://news24.gruposio.es/nue/videos-alcoyano-v-huesca-v-es-es-1ugs-17.php

here are many technical aspects that involve the use of fonts, but in this article, I would like to explore the more artistic outlook. In the following segments, I explain six typographic fundamentals to produce a more usable and engaging experience.

The method mentioned above is one of the ways to compute the autocorrect problem with the help of machine learning algorithms like logistic regression or Naive Bayes. However, even methods of deep learning can also be used to solve such similar problems. If you guys are interested, then let me in the comments below, and I will make an article covering the following in further detail.

The haar cascade classifier can be used for the purpose of face detection and accurately detect multiple faces in the frame. The haar cascade classifier for frontal face is usually an XML file that can be used with the open-cv module for reading the faces and then detecting the faces. A machine learning model such as the histogram of oriented gradients (H.O.G) which can be used with labeled data along with support vector machines (SVM’s) to perform this task as well.

Hi, I’m Dave and I coach founders that want to become great CEOs. Over the last 10 years, I’ve co-founded three VC-backed companies, invested in startups as a VC and Angel investor, and mentored hundreds of startups with Google and Techstars. Learn more about working with me at Dave-Bailey.com.

The best approach for face recognition is to make use of the DNN’s (deep neural networks). After the detection of faces, we can use the approach of deep learning to solve face recognition tasks. There is a huge variety of transfer learning models like VGG-16 architecture, RESNET-50 architecture, face net architecture, etc. which can simplify the procedure to construct a deep learning model and allow users to build high-quality face recognition systems.

The strange truth about emotionally-charged issues is that sometimes just being listened to solves the problem. Not always, but often. The question is, can you afford to take one hour out of your week to listen to your teammates? Or rather, can you afford not to?

Autocorrection, also known as text replacement, replace-as-you-type or simply autocorrect, is an automatic data validation function commonly found in word processors and text editing interfaces for smartphones and tablet computers.

Zero-shot and one-shot learning methods even exist for natural language processing. The same methods can be used for better training of the model to improve the overall performance and avoid repeated training procedures which can be a really big hindrance in some real-life applications and scenarios. Hence, one-shot learning is a great alternative for deployment and working in other embedded systems with lower training capacities.

2. Also, it requires an initial value. Because SharedFlow does not have .value, it does not need to be instantiated with an initial value — collectors will just suspend until the first value appears, and no one will try to access .value before any value arrives. If you don’t have an initial value for StateFlow you’ll have to make the StateFlow type nullable T? and use null as the initial value (or declare a sealed class for a default no-value value).

The next word prediction for a particular user’s texting or typing can be awesome. It would save a lot of time by understanding the user’s patterns of texting. This could be also used by our virtual assistant to complete certain sentences. Overall, the predictive search system and next-word prediction is a very fun concept to implement. You can check out my article below, which covers the deep learning methodology to predict the next words.

Face recognition is the procedural recognition of a human face along with the authorized name of the user. Face detection is a simpler task and can be considered as a beginner level project. Face detection is one of the steps that is required for face recognition. Face detection is a method of distinguishing the face of a human from the other parts of the body and the background.

The process of autocorrect involves four main steps, namely, identifying a misspelled word, then finding the strings while computing the minimum edit distance from each of them, filtering the possible candidates for the right word selection. And finally, calculating the word probabilities to forecast the best possible prediction for the particular word.

Hi, I’m Dave and I coach founders that want to become great CEOs. Over the last 10 years, I’ve co-founded three VC-backed companies, invested in startups as a VC and Angel investor, and mentored hundreds of startups with Google and Techstars. Learn more about working with me at Dave-Bailey.com.

Autocorrect based on AI methodologies is highly beneficial to achieve the best results while texting or typing to avoid incorrect statements or words. The spellings are automatically checked, and they are immediately corrected to the nearest right values. However, if the quality of your AI trained is not up to the mark leading to certain errors can be caused, and you might end up sending a message you did not want. Jokes aside, For the most part, autocorrect does a tremendous job in correcting misspelled words while texting quickly.