Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If you’re not an expert on AI or ML, don’t worry — we’re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney (@lmoroney).

In the last couple of episodes you saw how to tokenize text into numeric values and how to use tools in TensorFlow to regularize and pad that text. Now that we’ve gotten the preprocessing out of the way, we can next look at how to build a classifier to recognize sentiment in text.

Colab → https://goo.gle/tfw-sarcembed
GitHub → https://goo.gle/2PH90ea

NLP Zero to Hero playlist → https://goo.gle/nlp-z2h
Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow

Bio
Oriol Vinyals is a Principal Scientist at Google DeepMind, and a team lead of the Deep Learning group. His work focuses on Deep Learning and Artificial Intelligence. Prior to joining DeepMind, Oriol was part of the Google Brain team. He holds a Ph.D. in EECS from the University of California, Berkeley and is a recipient of the 2016 MIT TR35 innovator award. His research has been featured multiple times at the New York Times, Financial Times, WIRED, BBC, etc., and his articles have been cited over 70000 times. His academic involvement includes program chair for the International Conference on Learning Representations (ICLR) of 2017, and 2018. He has also been an area chair for many editions of the NeurIPS and ICML conferences. Some of his contributions such as seq2seq, knowledge distillation, or TensorFlow are used in Google Translate, Text-To-Speech, and Speech recognition, serving billions of queries every day, and he was the lead researcher of the AlphaStar project, creating an agent that defeated a top professional at the game of StarCraft, achieving Grandmaster level, also featured as the cover of Nature. At DeepMind he continues working on his areas of interest, which include artificial intelligence, with particular emphasis on machine learning, deep learning and reinforcement learning.

Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If you’re not an expert on AI or ML, don’t worry — we’re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney (@lmoroney).

In this first lesson we’ll talk about how to represent words in a way that a computer can process them, with a view to later training a neural network to understand their meaning.

Hands-on Colab → https://goo.gle/2uO6Gee

NLP Zero to Hero playlist → https://goo.gle/nlp-z2h
Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow

Computer Networks: Network Protocols and Communications in Computer Networks
Topics discussed:
1) Devices or Nodes.
2) Media, Cables, and Waves.
3) Services.

Follow Neso Academy on Instagram: @nesoacademy (https://bit.ly/2XP63OE)

Contribute: http://www.nesoacademy.org/donate

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Music:
Axol x Alex Skrindo – You [NCS Release]

#ComputerNetworksByNeso #ComputerNetwork #NetworkProtocols #Communications

Computer Networks:
Basics of Cisco Packet Tracer (Part 1)
Topics discussed:
1) The download procedure of Cisco Packet Tracer.
2) The basics of Cisco Packet Tracer.
3) Example packet tracer peer-to-peer network.

Follow Neso Academy on Instagram: @nesoacademy (https://bit.ly/2XP63OE)

Contribute: http://www.nesoacademy.org/donate

Memberships: https://bit.ly/2U7YSPI

Books: http://www.nesoacademy.org/recommended-books

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Forum ► https://forum.nesoacademy.org/
Facebook ► https://goo.gl/Nt0PmB
Twitter ► https://twitter.com/nesoacademy

Software source: www.netacad.com

Music:
Axol x Alex Skrindo – You [NCS Release]

#ComputerNetworksByNeso #ComputerNetwork #CiscoPacketTracer

Geordie Rose Interview part 6-6
Discussion about D-Wave and quantum computing
http://www.imminst.org

Youtube made me remove the Cube movie trailer because of copyright, so check it out here : https://www.youtube.com/watch?v=Esjc0rPj3K4

PS – the lengths of these videos could not be more synchronistic, original time before I was forced to cut out trailer was 33:47.

I know this is a longer video but I advise you watch it all, its a pretty complex idea and it has been discussed frequently over the years by different researchers. I have tried to pull together all the necessary information to give you a general overview of the theory.

Geordie Rose – Quantum Computing: Artificial Intelligence Is Here:
https://www.youtube.com/watch?v=PqN_2jDVbOU

Ringmakers of Saturn PDF:
https://podcast.sjrdesign.net/files/070_RingmakersOfSaturn.pdf

If you are interested in learning more about these idea’s head over to PastSaturnsRings on Reddit:
https://www.reddit.com/r/PastSaturnsRings/

Also check out Nick Hinton’s thread:
https://twitter.com/nickhintonn/status/1151986453569605632?lang=en

Part 2 will be out soon.

Support the Channel: https://www.patreon.com/zachstar
PayPal(one time donation): https://www.paypal.me/ZachStarYT

Part 1: https://www.youtube.com/watch?v=JRHAM1nAuD4

Follow me on Instagram: https://www.instagram.com/zachstar/
Twitter: https://twitter.com/ImZachStar

This video be in less depth than the previous but will cover a wider range of topics and research in artificial intelligence.

Startups in artificial intelligence are becoming more and more popular (over 100 just in healthcare) and they are all working on a variety of projects.

In this video I talk about large companies like google, facebook, and IBM and what projects they are working on in machine learning and other aspects of artificial intelligence.

One of the biggest breakthroughs in machine learning was when AlphaGo beat the best human go player in the world 4 out of 5 games. AlphaGo is a project that was programmed simply to learn, it wasn’t given any strategy or told what to do. This win showed that a computer could learn how to beat a human in the most complex game out there.

While a lot of this may seem really interesting, there is a lot of fear around A.I. as well in terms of what the future holds and where A.I. will go.

GPU Technology Conference 2017 kicks off with a powerful video showing how AI is changing our world. NVIDIA CEO and founder Jensen Huang welcomes the thousands of attendees to the largest gathering of GPU developers each year.

Contact Us : rajadeva.d@gmail.com

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Geordie Rose, DWAVE, Artificial Intelligence , KINDRED. https://www.youtube.com/watch?v=cD8zGnT2n_A&t=642s
https://en.wikipedia.org/wiki/H._P._Lovecraft#Biography
#idonotconcent
#thehelp
#news

#Freelancing #FreelanceDataScience #Upwork

Want to get started with freelancing in machine learning but don’t know where to start?

In my new series I’ll break it all down for you. What platform to use, how to write your profile, how to screen clients, how to apply to jobs, and how to deliver.

Stay tuned for more episodes.

Learn how to turn deep reinforcement learning papers into code:

Deep Q Learning:
https://www.udemy.com/course/deep-q-learning-from-paper-to-code/?couponCode=DQN-NOV-2020

Actor Critic Methods:
https://www.udemy.com/course/actor-critic-methods-from-paper-to-code-with-pytorch/?couponCode=AC-NOV-2020

Reinforcement Learning Fundamentals
https://www.manning.com/livevideo/reinforcement-learning-in-motion

Come hang out on Discord here:
https://discord.gg/Zr4VCdv

Website: https://www.neuralnet.ai
Github: https://github.com/philtabor
Twitter: https://twitter.com/MLWithPhil

Filmed at the NAV People’s Annual User Day on Tuesday 14th November 2017, we present the second part of the keynote session on Dynamics 365.

In this segment, you will learn the basics of Natural Language Generation and the Integration between TIBCO Spotfire and Automated Insights’s Natural Language Generation Software Wordsmith.

Filmed at the NAV People’s Annual User Day on Tuesday 14th November 2017, we present the fourth part of the keynote session on Microsoft Bookings.

This session took place in February 2016.

Part 1 of 7 – Speaker: Dr Maja Pantic, Professor of Affective Behavioural Computing, Imperial College London

Data mining, machine learning and artificial intelligence are becoming the most talk-about topics in digital health. With vast volumes of medical data available, exploiting these techniques to derive valuable insights may both challenge and reshape certain elements of our healthcare system.

These new approaches are leading to redefining drug discovery, assisting and automating diagnoses and helping predict and prevent diseases using health record data – or even our digital footprint. Artificially intelligent algorithms will permeate both the lives of the doctor and patient.

But there remains much hype, confusion and misunderstanding in the field. What is possible and what are the limitations? How will medicine adapt and what will be the impact on patient’s health and autonomy?

A commentary on some of the critical flaws and questions raised by Sam Harris’ argument for Strong Artificial Intelligence on JRE #940.

Part 3: Panel Discussion and Questions

The NBMBAA SF Chapter sponsored a panel to discuss the issues around machine learning, career and business.
Location: San Francisco
Panelists included:

Emmanuel Matthews – Google
Ayori Selassie – Salesforce
William Ford, PhD
Keita Broadwater, PhD – Oxygen AI
The moderator was Steven Bryant

Oxygen AI Home: https://www.oxygen-ai.com

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

– Natural Language Processing (Part 1): Introduction to NLP & Data Science
– Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
– Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
– Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
– Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
– Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial

For downloadable versions of these lectures, please go to the following link:

http://www.slideshare.net/DerekKane/presentations
https://github.com/DerekKane/YouTube-Tutorials

This is an introduction to text analytics for advanced business users and IT professionals with limited programming expertise. The presentation will go through different areas of text analytics as well as provide some real work examples that help to make the subject matter a little more relatable. We will cover topics like search engine building, categorization (supervised and unsupervised), clustering, NLP, and social media analysis.

Learn more on our blog: http://nvda.ly/WUV2T. NVIDIA CEO Jen-Hsun Huang describes the platforms NVIDIA is providing for PCs, drones, in the cloud or in cars to bring artificial intelligence to the world, at the Consumer Electronics Show 2016 in Las Vegas.

Part 2 of the Watson Virtual Agent series that shows how to integrate the Watson Virtual Agent solution into your own website. We take a simple Node.js application UI and with a few lines of code, can integrate our virtual agent. Feel free to ask any questions

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

– Natural Language Processing (Part 1): Introduction to NLP & Data Science
– Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
– Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
– Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
– Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
– Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial

Geordie Rose Interview part 4-6
Discussion about D-Wave and quantum computing
http://www.imminst.org

This simple video covers the very basics of predicate logic ( first order logic) used in knowledge representation . It starts with operators and covers examples later.

Machine Learning represents a new paradigm in programming, where instead of programming explicit rules in a language such as Java or C++, you build a system which is trained on data to infer the rules itself. But what does ML actually look like? In part one of Machine Learning Zero to Hero, AI Advocate Laurence Moroney (lmoroney@) walks through a basic Hello World example of building an ML model, introducing ideas which we’ll apply in later episodes to a more interesting problem: computer vision.

Try this code out for yourself in the Hello World of Machine Learning → https://goo.gle/2Zp2ZF3

This video is also subtitled in Chinese, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish.

Watch more Coding TensorFlow → https://bit.ly/Coding-TensorFlow
Subscribe to the TensorFlow channel → http://bit.ly/2ZtOqA3

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

– Natural Language Processing (Part 1): Introduction to NLP & Data Science
– Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
– Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
– Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
– Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
– Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial

In Part 1 of our 3 part interview, Jürgen Schmidhuber begins with an overview of what artificial intelligence is, describes his work at the Swiss Laboratory of Artificial Intelligence, and gives his opinion on the idea of a “singularity” in the future.
For the rest of the interview, and to see extra content from Part 1, go to http://www.Kidela.com

This episode is all about taking your AE2 game to the next level. We’ll cover Quantum Link chambers which allow you to transmit your network wirelessly over an infinite distance, even cross-dimensionally! We’ll also dabble in a little bit of sub-networking but the majority of the video is devoted to the power of P2P tunnels which allow for some seriously compact setups.

[QUICK JUMP]
0:15 – Quantum Link Chambers
2:52 – P2P Tunnels (all variants except ME)
7:55 – P2p Tunnels – ME
14:16 – Sub Networks
18:13 – Visualizing P2P & Compact setups

[More AE2 Tutorials]
AE2 – EP01 – A Beginner’s Guide – https://youtu.be/AjrMS4EhBEU
AE2 – EP02 – Your First Network – https://youtu.be/sD2GknUv1cM
AE2 – EP03 – Autocrafting – https://youtu.be/os5EYegEudE

P2P Conversion Recipes:
http://ae-mod.info/P2P-Tunnel/

[MODPACK & MOD VERSION]
DW20 1.12
Applied Energistics 2 rv5-stable-4

ABOUT US]
We are TheMindCrafters and we make tutorials/LPs/and Spotlights on our favorite (and guest requested) Minecraft mods, blocks, and modpacks
Our Site – http://theMindCrafters.com
Live Chat – http://theMindCrafters.com/#chat

After browsing and trying out over 4 different courses from multiple learning platforms this course from PY4E really stood out. Without any programming knowledge, I used this course to build my own payroll and incentive calculation system for my organization that employs over 100 people. Course Curator Certified Best Python Cousre on the Web. Dr. Charles Severance is truely a gifted educator who can simplify complex topics in to easy to USE, bite sized episodes that help you learn whats needed to start building applications right away!
Please visit https://www.py4e.com/ to get additional information on the course.
You can take this course for a certificate as the Python for Everybody Specialization on Coursera at https://www.coursera.org/specializations/python

Overview and demo of using Apache OpenNLP library in R to perform basic Natural Language Processing (NLP) tasks like string tokenizing, word tokenizing, Parts of Speech (POS) tokenizing

This is a getting started guide covering demos of OpenNLP coding in R

AI (artificial intelligence)

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple’s Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.

Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.

While AI tools present a range of new functionality for businesses ,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely.

Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in general. Researchers and marketers hope the label augmented intelligence, which has a more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them.

Music Credit :
Martian Cowboy Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 3.0 License
http://creativecommons.org/licenses/b… http://incompetech.com/ http://audionautix.com/ http://audionautix.com/

Part of Speech tagging does exactly what it sounds like, it tags each word in a sentence with the part of speech for that word. This means it labels words as noun, adjective, verb, etc. PoS tagging also covers tenses of the parts of speech.

This is normally quite the challenge, but NLTK makes this pretty darn simple!

sample code: http://pythonprogramming.net
http://hkinsley.com
https://twitter.com/sentdex
http://sentdex.com
http://seaofbtc.com

I’m showing how to setup the Virtual Agent on your personal dev, how to activate the OOB conversations (topics) and how to make it work on your Service Portal.
Part 2: https://www.youtube.com/watch?v=YZvCJahzZ7k

Record on the London release.

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