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Deep Learning and Computer Vision with Python Path (4.6) Path with 3 Courses: 19 interactive Videos. 192 Exercises. 36 Tutorials. 3 Projects. Research Paper Lists. Deep Learning Top Research Papers List (4.5) 17 Tutorials. Curated list of research paper summaries by subfield. 4 minute read. Show recent activity Deep Learning for Community Detection: Progress, Challenges and Opportunities Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, Philip S Yu. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Deep Learning for Community Detection: Progress, Challenges and Opportunities Fanzhen Liu 1, Shan Xue;2, Jia Wu1, Chuan Zhou3, Wenbin Hu4, Cecile Paris2; 1, Surya Nepal2;1, Jian Yang , Philip S. Yu5 1 Department of Computing, Macquarie University, Sydney, Australia 2 CSIRO's Data61, Sydney, Australia 3 Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, Chin Deep Learning Community. 2,534 likes · 8 talking about this. Community with actual news and discussions about Artificial Intelligence. No flood and noise. Subscribe and enjoy

Deep Learning Community CommonLoung

  1. Deep Learning. 12606 members. Follow. Intuition behind concepts. Research paper summaries and discussion. Links to tools, datasets, code and other resources. Share this. Show community info
  2. As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and data analytics. However, the classic methods of community detection, such as spectral clustering and statistical inference, are falling by the wayside as deep learning techniques demonstrate an increasing capacity to.
  3. Deep Learning community has 323 members. Join this group to post and comment
  4. Deep Learning Techniques for Community Detection in Social Networks Abstract: Graph embedding is an effective yet efficient way to convert graph data into a low dimensional space. In recent years, deep learning has applied on graph embedding and shown outstanding performance
Deep Learning & Artificial Intelligence Solutions from NVIDIA

Deep Learning for Community Detection: Progress

Show community info. Main. CommonLounge is a community of learners who learn together. An introduction to Deep Learning + tutorial on getting started with TensorFlow by the Google Cloud team. Read more(17 words) Learn TensorFlow and deep learning, without a Ph.D Deep learning is a class of machine learning algorithms that (pp199-200) uses multiple layers to progressively extract higher-level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces.. Overview. Most modern deep-learning models are based on. Deep Learning. 12647 members. Follow. Intuition behind concepts. Research paper summaries and discussion. Links to tools, datasets, code and other resources. Share this. Show community info

Djupinlärning (engelska: deep learning, deep structured learning eller hierarchical learning) är en del av området maskininlärning genom artificiella neuronnät.Djupinlärning är baserat på en uppsättning algoritmer som försöker modellera abstraktioner i data på hög nivå genom att använda många processlager med komplexa strukturer, bestående av många linjära och icke-linjära. Deep Learning. 12638 members. Follow. Intuition behind concepts. Research paper summaries and discussion. Links to tools, datasets, code and other resources. Share this. Show community info Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. This website is intended to host a variety of resources and pointers to information about Deep Learning. In these pages you will find. a reading list

Heroes of NLP is a video interview series featuring Andrew Ng, the founder of DeepLearning.AI, in conversation with thought leaders in NLP. Watch Andrew lead an enlightening discourse around how these industry and academic experts started in AI, their previous and current research projects, how their understanding of AI has changed through the decades, [ Deep learning is one of the hottest fields in data science with many case studies that have astonishing results in robotics, image recognition and Artificial Intelligence (AI). One of the most powerful and easy-to-use Python libraries for developing and evaluating deep learning models is Keras; It wraps the efficient numerical computation libraries Theano and TensorFlow

Deep Learning Community - Home Faceboo

  1. Tip: for a comparison of deep learning packages in R, read this blog post.For more information on ranking and score in RDocumentation, check out this blog post.. The deepr and MXNetR were not found on RDocumentation.org, so the percentile is unknown for these two packages.. Keras, keras and kerasR Recently, two new packages found their way to the R community: the kerasR package, which was.
  2. Welcome to the deeplearning.ai community! We're a global, diverse network of deep learners passionate about learning and building AI. Our meetup series, Pie & AI, typically includes conversations with AI leaders, thought-provoking discussions, networking opportunities, hands-on project practice, and pie
  3. 4 Deep Learning Approach to Community Detection The basic idea adopted in the literature [ 20 ] is to substitute factorization based reconstruction methods with non-linear models like autoencoders. In the following sections we introduce autoencoder and discuss these models in detail
  4. Deep Learning Community India. 725 likes · 3 talking about this. Community is dedicated to techies aware of latest Deep learning happening framework, Library, startups, courses, Institutes,Training,..
  5. Similar to machine learning, deep learning also has supervised, unsupervised, and reinforcement learning in it. As discussed earlier, the idea of AI was inspired by the human brain. So, let's try to connect the dots here, deep learning was inspired by artificial neural networks and artificial neural networks commonly known as ANN were inspired by human biological neural networks

Python has an extensive library that supports functions for Deep Learning, Machine learning and Artificial Intelligence. It has got a strong Python community around to help its users get the essential support if faced with a problem Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new superpower that will let you build AI systems that just weren't possible a few years ago. In this course, you will learn the foundations of deep learning Read writing about Deep Learning in Google Cloud - Community. A collection of technical articles and blogs published or curated by Google Cloud Developer Advocates. The views expressed are those.

[2005.08225] Deep Learning for Community Detection ..

Deep Learning, Kawasaki. 14,180 likes · 38 talking about this · 2 were here. Computer Compan Deep Learning (DL) has become more than just a buzzword in the Artificial Intelligence (AI) community - it is reshaping global business through the prolific use of autonomous, self-teaching systems, which can build models by directly studying images, text, audio, or video data Deep learning community in Nancy. Blog About. Machine Learning course. The dates of the course 12/11 A101; 03/12 (exam) A007; Here is the syllabus of a course on Machine Learning that I'm teaching in 2018-2019: Machine learning introduction (for a printable version Deep neural networks convex optimization: line search, steepest. | Distributed (Deep) Machine Learning Common . DMLC is a community hosting and developing portable, scalable and reliable open source libraries for distributed machine learning. All projects are licenced under Apache 2.0. Contributors come from leading universities and companies

Deep Learning: The Latest Trend In AI And ML | Qubole

Most deep learning methods use neural network architectures, which is why deep learning models are often referred to as deep neural networks.. The term deep usually refers to the number of hidden layers in the neural network. Traditional neural networks only contain 2-3 hidden layers, while deep networks can have as many as 150.. Deep learning models are trained by using large sets of. Deep learning packages for R. Machine Learning and Modeling. karansehgal1988 May 19, 2019, 5:01pm #1. What is the difference between nnet and keras package in R for neural networks and which package is the best for neural networks. Best deep Learning Package. karansehgal1988

Deep Learning community Public Group Faceboo

The simple Deep Learning operator gives you different activation functions and the ability to add dropout layers. There are also some advanced parameters that allow you to fine tune the algorithm performance which you can read about in the H2O documentation online Wabisabi is the premier Professional Learning Community for educators and leaders. Facilitated by best-selling author and keynote speaker Lee Watanabe-Crockett with his team of master teachers and thought leaders, this global community brings together those passionate about the education of young people to engage in joyful curiosity and learn from one another's stories, experiences, and ideas A discussion for people to introduce themselves. Share your level of expertise, what you're looking for in this community, how you got started in deep learning, or anything else you'd like Deep learning (DL) models for disease classification or segmentation from medical images are increasingly trained using transfer learning (TL) from unrelated natural world images. However, shortcomings and utility of TL for specialized tasks in the medical imaging domain remain unknown and are based on assumptions that increasing training data will improve performance. We report detailed.

Deep Learning Techniques for Community Detection in Social

  1. As deep learning algorithms can learn high-level features which are more tolerant to the variations of nuisance factors, and have achieved success in various computer vision tasks, they have recently received significant attention from the research community
  2. For those looking for Spatial Deep Learning and GeoAI Resources, the following provides beginner-to-Pro list for different Imagery Deep Learning, GeoAI, ArcGIS Notebooks examples and other resources in the format of quick overview, videos, articles and sample notebooks. Part 1: Quick overview (8.
  3. When Deep Learning Weekly's original curators, Malte Baumann and Jan Bussieck, approached us about reviving the newsletter and community, we were thrilled at the opportunity. We saw how much their mission aligned with our own: to create an open, inclusive space for anyone interested in machine learning or mobile development to create, collaborate, and inspire one another
  4. Deep Learning Adventures. Join our Deep Learning Adventures community and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forecasting All while having fun learning and.
  5. Read writing about Deep Learning in Clique Community. Clique is an initiative by young women developers dedicated to break-off the gender gap in tech field and give rise to a strong community who.
  6. SASVBA Provides Best Deep Learning Training in Delhi/NCR with Latest Development Environment and Frameworks. We keep Our Courses Up to Date with the Latest industrial trends. SASVBA Is One of the best training Deep Learning Institute in Delhi/NCR Which Helps Students to Crack Interviews in Tech Giants

Learning community members strive to refine their collaboration, communication, and relationship skills to work within and across both internal and external systems to support student learning. They develop norms of collaboration and relational trust and employ processes and structures that unleash expertise and strengthen capacity to analyze, plan, implement, support, and evaluate their practice COMMUNITY ABOUT SUPPORT Install Steam | language. Deep Learning Player Deep Learning Player. Poland Level . 68. Miyako. 500 XP . TOMORROW IS IN YOUR HANDS. View more info. Currently Online. Badges 34 Inventory Screenshots 818 Reviews. Offered by DeepLearning.AI. If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new superpower that will let you build AI systems that just weren't possible a few years ago Deep learning neural networks are ideally suited to take advantage of multiple processors, distributing workloads seamlessly and efficiently across different processor types and quantities. With the wide range of on-demand resources available through the cloud, you can deploy virtually unlimited resources to tackle deep learning models of any size

Deep learning - Wikipedi

For those looking for Spatial Deep Learning and GeoAI Resources, the following provides beginner-to-Pro list for different Imagery Deep Learning, GeoAI, ArcGIS Notebooks examples and other resources in the format of quick overview, videos, articles and sample notebooks This Deep Learning course with Tensorflow certification training is developed by industry leaders and aligned with the latest best practices. You'll master deep learning concepts and models using Keras and TensorFlow frameworks and implement deep learning algorithms, preparing you for a career as Deep Learning Engineer

Djupinlärning - Wikipedi

  1. Dive into Deep Learning. Interactive deep learning book with code, math, and discussions Implemented with NumPy/MXNet, PyTorch, and TensorFlow Active community support. You can discuss and learn with thousands of peers in the community through the link provided in each section
  2. Deep Cognition is an Edge AI powered platform and buisness solution provider. Deep Learning Studio gives users easy access to a GUI for deep learning
  3. Online Learning. Deep Learning Onramp This free, two-hour deep learning tutorial provides an interactive introduction to practical deep learning methods. You will learn to use deep learning techniques in MATLAB for image recognition
  4. DEEP LEARNING Deep learning is a subset of AI and machine learning that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, language translation, and others. Deep learning differs from traditional machine learning techniques in that they can automatically learn representations from data suc
  5. g language which implements neural networks, a main area of deep learning research
  6. Hair & Beauty Community. The Hair & Beauty Community is exclusive to students using Skin Deep Learning materials and is designed to encourage student engagement in the learning process. Find out more. Annual Update. Each year, selected Units of Competency (UOC) are updated to assist you in your obligation for continuous improvement

Video: Deep Learning

MATLAB + Deep Learning Toolbox MathWorks: Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder: Yes: Yes: Yes: Yes: Yes With Parallel Computing Toolbox: Yes Microsoft Cognitive Toolkit (CNTK) Microsoft Research: 2016 MIT license: Ye Practical Deep Learning for Coders (2020 course, part 1): Incorporating both an introduction to machine learning, and deep learning, and production and deployment of data products Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD : A book from O'Reilly, which covers the same material as the course (including the content planned for part 2 of the course

Homepage - New Pedagogies for Deep Learning

Yann LeCun, the chief AI scientist at Facebook, helped develop the deep learning algorithms that power many artificial intelligence systems today. In conversation with head of TED Chris Anderson, LeCun discusses his current research into self-supervised machine learning, how he's trying to build machines that learn with common sense (like humans) and his hopes for the next conceptual. Deep Learning for Community Detection: Progress, Challenges and Opportunities. In Christian Bessiere , editor, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020 [scheduled for July 2020, Yokohama, Japan, postponed due to the Corona pandemic] Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs Today's selection of articles from Kotaku's reader-run community: Is Deep Learning AI The Solution To Next-Gen Conversations? • Developer Journal Mega Update #11 • TAY Retro: Famicom - Rockman 6 (Mega Man 6) [TV Commercial (JP) Deep Learning: Keras-Tensorflow-OpenCL. Discussion created by bellisano on Sep 5, 2018 Latest reply on Sep 13, 2018 by bellisano. Comment • 3; Hi boys, I'm learning to use Keras with tensorflow but I do not have a geforce graphics card and I can not use cuda

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Using Deep Learning for Community Discovery in Social

  1. There are over 35 new deep learning related examples in the latest release. That's a lot to cover, and the release notes can get a bit dry, so I brought in reinforcements. I asked members of the... read more >>
  2. What is Deep Learning and How Does Deep Learning Work Lesson - 1. What is Neural Network: Overview, Applications, and Advantages Lesson - 2. Neural Networks Tutorial Lesson - 3. Top 8 Deep Learning Frameworks Lesson - 4. Top 10 Deep Learning Algorithms You Should Know in (2020) Lesson - 5. What is Tensorflow: Deep Learning Libraries and Program.
  3. g. How can you tell if you are actually engaged in deep learning? Dr. Bain offers the following classification of learners: Surface learners: They do as little as possible to get by. Strategic learners: They aim for the highest grades rather than for true.
  4. Deep Reinforcement Learning Course is a free course (articles and videos) about Deep Reinforcement Learning, where we'll learn the main algorithms, and how to implement them in Tensorflow and PyTorch
  5. Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. If you're looking to dig further into deep learning, then -learning-with-r-in-motion>Deep Learning with R in Motion</i></a> is the perfect next step
  6. Deep Learning with PyTorch will first provide students with a theoretical understanding of simple neural nets and then gradually move to explore Deep Neural Nets and Convolutional Neural Networks. It will then give them hands-on experience for successfully training Deep Neural Networks, which requires a significant amount of time and compute
  7. 3D deep learning is used in a variety of applications including robotics, AR/VR systems, and autonomous machines. In this month's Jetson Community Project spotlight, researchers from MIT's Han Lab developed an efficient, 3D, deep learning method for 3D object segmentation, designed to run on edge devices. We present Point-Voxel CNN (PVCNN) for efficient, fast 3D deep learning

For over a decade, Microsoft researchers have worked on Project InnerEye—technology to help analyze 3D medical imaging with machine learning. Learn about their new open-source deep learning toolkit to allow clinical & research teams to create ML models Hello, I am new to Intel development environments. In my project, I aim to download a deep learning inference solution to a Kintex-7 FPGA on NI CompactRIO-9040 I wanted to know whether it is possible to do this within the OpenCL framework, possibly using some Intel SDK or other software. I can also. I feel like the criteria for research in deep learning have been set to be unrealistic for anyone other than the big tech companies to publish a paper. I have been reading reviews that include The authors didn't try experiment X,Y,Z. and go entirely based on impressive results that lack true novelty and are only achieved due to how much computation was thrown at the problem Python & Machine Learning (ML) Projects for $10 - $30. I tried coding up my own deep Q learning agent for a custom openAI gym env but need some help (either tutoring or freelancing) by tomorrow or early tomorrow preferably. The deep q learning agent needs..

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Skymind is releasing its bundle of deep-learning libraries as a free community edition tomorrow. This move is meant to help bring machine learning capabilities to enterprises using Java Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105. info@databricks.com 1-866-330-012

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Deep learning community in Nancy. The deeploria group (and this website) is nearly inactive currently, because I've been focusing all my efforts on another project: OLKi FWCS is on a mission to educate all students to high standards, enabling them to become productive, responsible citizens. Deep Learning is how we're doing it Description. This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition A collection of lectures on deep learning, deep reinforcement learning, autonomous vehicles, and artificial intelligence organized by Lex Fridman The Deep Learning community is currently (March 2017) in a race to train computers to beat people at almost any game you can think of, including: Space Invaders, Doom, Pong, Gathering and dozen of other games

Deep Learning - community-z

Community Dev Series: Learning about Deep Learning: Applications for OpenJDK/Java Verification Build, test, and leverage technological solutions to combat systemic racism Get involved Close outlin Deep Learning An MIT Press book in preparation Ian Goodfellow, Yoshua Bengio and Aaron Courville. Book Exercises Lectures. External Links. Commonlounge community for discussing the book; Reading group videos for every chapter, from a reading group organized by Alena Kruchkova. In this learning path, you will be able to learn the basic concepts of Deep Leaning and TensorFlow. Then, you will get hands-on experience in solving problems using Deep Learning. Starting with a simple Hello Word example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, [

Welcome to CS147! Over the past few years, Deep Learning has become a popular area, with deep neural network methods obtaining state-of-the-art results on applications in computer vision (Self-Driving Cars), natural language processing (Google Translate), and reinforcement learning (AlphaGo) An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. Written by three experts in the field, Deep Learning is the only comprehensive book on the subject. —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceXDeep learning is a form of machine. Our pioneering research includes deep learning, reinforcement learning, theory & foundations, neuroscience, unsupervised learning & generative models, control & robotics, and safety Deep learning framework by BAIR. Created by Yangqing Jia Lead Developer Evan Shelhamer. View On GitHub; Caffe. Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley

Community Archives - deeplearning

Figure 1: The growth of deep learning model complexity. For most deep learning teams, the initial focus is on creating a model that obtains a high accuracy on their use case. Training a model to return a desired result with high accuracy is an accomplishment in and of itself. Model size, latency, and power consumption considerations come next The goal of this workshop is to establish a GDL community in Israel, get to know each other, and hear what everyone is up to. We hope the workshop will be successful and lead to similar events in the future, as well as a closer collaboration of the Israeli community. Topics. Deep learning on non-Euclidean domains, including: Set For any budding machine learning engineer, spending time in the AI blogosphere will not only help your prospects for career advancement but also keep you connected to the broader AI community. Related: 6 AI Trends to Watch for in 2019. However, there are tons of machine learning, artificial intelligence, and deep learning options out there Free zoom lecture about advances in deep learning and 3D modeling for reddit community going again Following the amazing turn in of redditors for this lecture (500 people registered O_O) We are having 4 more free zoom events for the reddit community

Keras Tutorial: Deep Learning in Python - DataCamp Community

Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win Not by learning how the clutch and the internal combustion engine work. Atleast not initially. When learning deep learning, we will follow the same top-down approach. Do the fast.ai course — Practical Deep Learning for Coders — Part 1. This takes about 4-6 weeks of effort. This course has a session on running the code on cloud We will step through a simple example of where and how to apply deep learning to more effectively test Java runtimes. By covering the basics of deep learning and the simple example, the intent of this presentation is to spark curiosity and generate ideas on future applications of this machine learning approach to problem-solving This topic has innovative mini ai projects in deep learning, machine learning (with source code) for ai ideas for beginners, students and talents. HOME COMMUNITY FORUM WIKI BLOG EDUCATION [[l.name]

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keras: Deep Learning in R - DataCamp Community

Intro to Deep Learning. Use TensorFlow and Keras to build and train neural networks for structured data. Intro to SQL. Learn SQL for working with databases, using Google BigQuery to scale to massive datasets. Advanced SQL. Take your SQL skills to the next level. Data Cleaning Deep learning, a subset of machine learning represents the next stage of development for AI. By using artificial neural networks that act very much like a human brain, machines can take data in. Algorithms that can learn from and make classifications and predictions on data. Related subjects of computer science, pattern recognition, computer vision, computational learning and statistics, probabilistic programming, and artificial intelligence. Wolfram Community threads about Machine Learning Dr. Ng added, Other deep learning platforms have been a great boon to researchers wanting to invent new deep learning algorithms. but their high degree of flexibility limits their ease of use At some point during your AI project, you will need to consider which machine learning framework to use. For some tasks, using traditional machine learning algorithms will be enough. However, if you work with a large collection of text, images, videos, or speech, deep learning is the way to go

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recently I see that NVIDIA has explicit support for Deep Learning frameworks, maybe all the major frameworks (Caffe, Theano,Thorch It looks like the Caffe work is just a request to check in basic OpenCL support, but work is underway in the community.. Deep learning es un área de reciente creación con una enorme popularidad. Deep learning busca el aprendizaje a partir de grandes volúmenes de datos y con ayuda de redes neuronales de gran tamaño. En este curso aprenderás que es una red neuronal, como crear una red neuronal, entrenar una red neuronal con un conjunto de imágenes Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides. Deep learning is beginning to impact biological research and biomedical applications as a result of its ability to integrate vast datasets, learn arbitrarily complex relationships and incorporate existing knowledge. Already, deep learning models can predict, with varying degrees of success, how gene The Deep Learning Institute will also introduce new courses to teach domain-specific applications of deep learning for finance, Shanahan sees Project Maven as a force that will ripple across the entire defense community. AI and machine learning, Shanahan said,. Equip yourself with in-demand skills in this online Deep Learning program from IBM to become a successful AI practitioner. Advance your career today

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