Studying the masters will help you understand how all copywriting elements fit together.

Vincent Berger a insisté pour sa part sur l’impact du numérique à l’Université.

To successfully learn something new, people must evaluate their understanding, monitor for confusion or inconsistency, plan what to do next based on those observations, and coordinate that plan’s execution. This often falls under the category of “metacognition,” though prefer to unbundle its phenomena.

If knowledge of one item makes it harder to remember another item, we have a case of memory interference.

Here again are the twenty rules of formulating knowledge.

If you see a word and immediately check it's translation, you'll hardly memorize it at all. If you try your best to recall what the word means before checking the translation, the chances of memorization are much better. It is much easier to memorize a word's meaning when you know how to pronounce it corretly, so get it right.  

Somewhere between too hard and too easy, there’s a sweet-spot where reviews are challenging enough to hold your interest, but not so hard that it feels like torture. When the challenge of reviews is just right, you’ll actually get a sense of accomplishment and a little jolt of dopamine as you do them. Our brains actually enjoy challenges as long as they aren’t too hard or too easy. As I see it, this level of challenge is where you want to be.

Researchers have found that reviews are more effective when they’re difficult. That is, if you have to work at remembering a card, it’ll have a stronger effect on your memory. The harder a review is, the more it boosts your memory. This is called “desirable difficulty” in the literature.

// ES5-compatible code var myObject = { prop1: 'hello', prop2: 'world', output: function() { console.log(this.prop1 + ' ' + this.prop2); } }; myObject.output(); // hello world

I also recently took about 10 months off of work, specifically to focus on learning. It was incredible, and I don’t regret it financially. I would often get up at 6 in the morning or even earlier (which I never do) just from excitement about what I was going to learn about and accomplish in the day. Spending my time focused Only on what I was most interested in was incredibly rewarding.

Talented people flock to employers that promise to invest in their development whether they will stay at the company or not.

We want to learn, but we worry that we might not like what we learn. Or that learning will cost us too much. Or that we will have to give up cherished ideas.

afternoons are spent reading/researching/online classes.This has really helped me avoid burn out. I go into the weekend less exhausted and more motivated to return on Monday and implement new stuff. It has also helped generate some inspiration for weekend/personal projects.

It is difficult to choose a typical reading speed, research has been conducted on various groups of people to get typical rates, what you regularly see quoted is: 100 to 200 words per minute (wpm) for learning, 200 to 400 wpm for comprehension.

Such languages may make it easier for a person without knowledge about the language to understand the code and perhaps also to learn the language.

Python contributed examples¶ Mic VAD Streaming¶ This example demonstrates getting audio from microphone, running Voice-Activity-Detection and then outputting text. Full source code available on https://github.com/mozilla/DeepSpeech-examples. VAD Transcriber¶ This example demonstrates VAD-based transcription with both console and graphical interface. Full source code available on https://github.com/mozilla/DeepSpeech-examples.

Python API Usage example Edit on GitHub Python API Usage example¶ Examples are from native_client/python/client.cc. Creating a model instance and loading model¶ 115 ds = Model(args.model) Performing inference¶ 149 150 151 152 153 154 if args.extended: print(metadata_to_string(ds.sttWithMetadata(audio, 1).transcripts[0])) elif args.json: print(metadata_json_output(ds.sttWithMetadata(audio, 3))) else: print(ds.stt(audio)) Full source code

DeepSpeech is an open source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. NOTE: This documentation applies to the 0.7.0 version of DeepSpeech only. Documentation for all versions is published on deepspeech.readthedocs.io. To install and use DeepSpeech all you have to do is: # Create and activate a virtualenv virtualenv -p python3 $HOME/tmp/deepspeech-venv/ source $HOME/tmp/deepspeech-venv/bin/activate # Install DeepSpeech pip3 install deepspeech # Download pre-trained English model files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.pbmm curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.scorer # Download example audio files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/audio-0.7.0.tar.gz tar xvf audio-0.7.0.tar.gz # Transcribe an audio file deepspeech --model deepspeech-0.7.0-models.pbmm --scorer deepspeech-0.7.0-models.scorer --audio audio/2830-3980-0043.wav A pre-trained English model is available for use and can be downloaded using the instructions below. A package with some example audio files is available for download in our release notes.

Speech & Machine Learning

import all the necessary libraries into our notebook. LibROSA and SciPy are the Python libraries used for processing audio signals. import os import librosa #for audio processing import IPython.display as ipd import matplotlib.pyplot as plt import numpy as np from scipy.io import wavfile #for audio processing import warnings warnings.filterwarnings("ignore") view raw modules.py hosted with ❤ by GitHub View the code on <a href="https://gist.github.com/aravindpai/eb40aeca0266e95c128e49823dacaab9">Gist</a>. Data Exploration and Visualization Data Exploration and Visualization helps us to understand the data as well as pre-processing steps in a better way. 

TensorFlow recently released the Speech Commands Datasets. It includes 65,000 one-second long utterances of 30 short words, by thousands of different people. We’ll build a speech recognition system that understands simple spoken commands. You can download the dataset from here.

Learn how to Build your own Speech-to-Text Model (using Python) Aravind Pai, July 15, 2019 Login to Bookmark this article (adsbygoogle = window.adsbygoogle || []).push({}); Overview Learn how to build your very own speech-to-text model using Python in this article The ability to weave deep learning skills with NLP is a coveted one in the industry; add this to your skillset today We will use a real-world dataset and build this speech-to-text model so get ready to use your Python skills!

Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research. Use Keras if you need a deep learning library that: Allows for easy and fast prototyping (through user friendliness, modularity, and extensibility). Supports both convolutional networks and recurrent networks, as well as combinations of the two. Runs seamlessly on CPU and GPU. Read the documentation at Keras.io. Keras is compatible with: Python 2.7-3.6.

Z gier można wyciągnąć też inną naukę. Jeśli Twoim celem jest przejście do następnej lokacji, to czy musisz wykonywać wszystkie zadania poboczne?No nie musisz. Dlatego wyżej, gdy podawałem wymagane umiejętności dla osoby, która prowadzi szkolenia z Reacta, albo pracuje dla startupów, to napisałem “dobra znajomość JSa”, bo “doskonała” nie pomoże Ci w osiągnięciu tego celu.

Installation in Windows Compatibility: > OpenCV 2.0 Author: Bernát Gábor You will learn how to setup OpenCV in your Windows Operating System!

Here you can read tutorials about how to set up your computer to work with the OpenCV library. Additionally you can find very basic sample source code to introduce you to the world of the OpenCV. Installation in Linux Compatibility: > OpenCV 2.0

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 18 million. The library is used extensively in companies, research groups and by governmental bodies. Along with well-established companies like Google, Yahoo, Microsoft, Intel, IBM, Sony, Honda, Toyota that employ the library, there are many startups such as Applied Minds, VideoSurf, and Zeitera, that make extensive use of OpenCV. OpenCV’s deployed uses span the range from stitching streetview images together, detecting intrusions in surveillance video in Israel, monitoring mine equipment in China, helping robots navigate and pick up objects at Willow Garage, detection of swimming pool drowning accidents in Europe, running interactive art in Spain and New York, checking runways for debris in Turkey, inspecting labels on products in factories around the world on to rapid face detection in Japan. It has C++, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS. OpenCV leans mostly towards real-time vision applications and takes advantage of MMX and SSE instructions when available. A full-featured CUDAand OpenCL interfaces are being actively developed right now. There are over 500 algorithms and about 10 times as many functions that compose or support those algorithms. OpenCV is written natively in C++ and has a templated interface that works seamlessly with STL containers.

Using objects as keys is one of most notable and important Map features.

Ce travail de programmation, de l’outil qu’il a fallut apprendre, a été nourri par la précieuse aide technique apportée par toute l’équipe de Canopé Versailles.

click

document.addEventListener("click", myFunction);function myFunction() {  document.getElementById("demo").innerHTML = "Hello World"; }

there is also strong encouragement to make code re-usable, shareable, and citable, via DOI or other persistent link systems. For example, GitHub projects can be connected with Zenodo for indexing, archiving, and making them easier to cite alongside the principles of software citation [25].

Did you expect the temp directory to get printed? In the last example, we saw the directories ./temp and ./C/temp got printed, but not now. This is the effect of the -print option. By default, the find command prints all the files matching the criteria. However, once the -print option is specified, it will print files only on explicit print instructions. In this find command, -print is associated in the other side of the OR condition, and hence nothing will get printed from the 1st part of the condition.

Trying too hard to understand the minutiae initially can make it easy to miss a fairly apparently general theme. It’s productive to learn the parts that are accessible before putting in effort to fully understand everything. Don’t miss the forest for the trees.

Highlights can be created by clicking the button.

For my more advanced students, they need to learn research skills: how to locate, evaluate, and use information. Online learning offers great opportunities for that, including with what’s going on in the news right now.

Then there is the option of getting students to talk to each other online on discussion boards and videoconferences. Some students adapt to it quickly and like it. Some don’t, because it feels impersonal. You have to be patient with that and give them some time and space to adjust.

Rizga: How have you been translating this online?Moore: It depends on the student. Some students work very well asynchronously. They are very comfortable working alone on a draft; I make color-coded comments in a word document or their PDF, and then I send it back. Some students need me to explain things to them in person before I send them the comments; we’ll do a video or audio chat. Others need even more interaction: I’ll hook them up to a videoconference, and we’ll go through all the comments together. Some students I need to refer to a grammar-brushup program or a YouTube video on how to do some of the mechanical stuff like uploading papers online.

The other big issue is that many of the teachers don’t have the skills to teach online.

We are in the midst of the most sweeping education experiment in history. The coronavirus pandemic has forced the majority of the U.S.’s 3.6 million educators to find ways to teach without what most of them consider the core part of their craft—the daily face-to-face interactions that help them elicit a child’s burning desire to investigate something; detect confusion or a lack of engagement; and find the right approach, based on a student’s body language and participation in the classroom, to help students work through their challenges.

Then, you have to think about accessibility issues. How will my vision-impaired and deaf students access it? Have I put everything in print? Do I have to put in some audio? There are whole series of checks you have to do for different access issues.

by everybody (Public)

adding tags

Assign students to do further research or fact checking on particular paragraphs or literature cited in the text and report their findings in an annotation.

Assign students to each choose a paragraph of the reading assignment and summarize the paragraph’s argumentation in an annotation.

ask discussion questions

a web tool that allows you to annotate

You can also switch to JavaScript to see the text-based code behind the blocks.

a black software developer embarrassed Google by tweeting that the company’s Photos service had labeled photos of him with a black friend as “gorillas.”

More than two years later, one of those fixes is erasing gorillas, and some other primates, from the service’s lexicon. The awkward workaround illustrates the difficulties Google and other tech companies face in advancing image-recognition technology

It doesn’t.What it does do is teach AI to recognize various things and fool you into thinking you’re getting better security.When you get something for free, you are the product.

Emerging Theories of Learning and the Role of Technology

In order to prepare students for the demands of this new century change in the way teaching and learning occurs must take place. Learning environments must become more authentic, by giving students the opportunities to use higher order thinking and problem solving skills connected to real world applications (Fouts, 2000).  It is this need along with the change in the current student population that has led to the rethinking of learning theories and the revamping of learning environments.  These new theories whose foundations are based on older educational theories are vastly different in their methods of teaching and learning.

Theories and Frameworks for Online Education: Seeking an Integrated Model

Research in Educational Technology

Integrating Technology in the Adult Education Classroom

Integrating EducationalTechnology into the Curriculum

A: Read an article from start to finish. ONLY THEN do you import parts into Anki for remembering B: Incremental Reading: interleaving between reading and remembering

“I think SM is only good for a small minority of learners. But they will probably value it very much.”

In Anki, you are only doing the remembering part. You are not reading anything new in Anki

Using either SRS has already given you a huge edge over not using any SRS: No SRS: 70 hours Anki: 10 hours SuperMemo: 6 hours The difference between using any SRS (whether it’s Anki or SM) and not using is huge, but the difference between Anki or SM is not

“Anki is a tool and SuperMemo is a lifestyle.”

The Cornell Note-taking System

And for the last three years, I've added EVERYTHING to Anki. Bash aliases, IDE Shortcuts, programming APIs, documentation, design patterns, etc. Having done that, I wouldn't recommend adding EVERYTHING

Habit: Whenever I search StackOverflow, I'll immediately create a flashcard of my question and the answer(s) into Anki.

The confidence of knowing that once something is added to Anki it won't be forgotten is intoxicating

Kyle had a super hero ability. Photographic memory in API syntax and documentation. I wanted that and I was jealous. My career was stuck and something needed to change. And so I began a dedicated journey into spaced repetition. Every day for three years, I spent one to three hours in spaced repetition

Infographics, Online, Learning, Engagement, Visual

Connected Learning

At GitLab, "no ego" means that we foster and support an environment where results matter, and you're given agency to approach your work in the way that makes sense to you. Instead of judging people for not approaching work in an agreed-upon way, "no ego" encourages people to glean inspiration from watching others approach work in new and different ways.

The Zettelkasten method makes reading complicated texts less frustrating. You’re not necessarily trying to understand the whole text. You’re just hunting down ideas to incorporate into your Zettelkasten. Who cares if you don’t understand everything? As long as you’re extracting some ideas, you’re growing your knowledge base and the text is being useful to you.

Reading doesn’t magically increase your knowledge. Just because some text has entered your eyeballs and visited your short-term memory, that doesn’t mean you’ve learned from it. In fact, if all you’re doing is reading — and you’re doing so for any purpose other than entertainment — then you’re wasting your time. What has only entered your short-term memory will eventually be forgotten and is useless in the long term. Years later, it’ll be as if you had never read that book or that article.

So this is one case where we could test and sort individuals to predict success in different learning tasks, something I talked about in this short article about helping students develop strategies for memorization. Perhaps researchers could tackle some other ways to harness the multiple capacities idea to steer students into the subjects and learning strategies that will work best for them.