Best Machine Learning and Deep Learning Courses, Tutorials, Training and Certification

Machine Learning and Deep learning are in boom nowadays in technical area. Many giant companies Google, Microsoft, Amazon and Uber are contributing a lot in these area. Machine Learning and Deep learning are extracting meaning and insights from massive data sets. Engineers who have experience in these field know as Data Scientists and this is top-paying jobs nowadays. Courseism.com experts team has analysed all learning websites and providing comprehensive and best machine learning and deep learning course for 2019 and 2020. In the list, it is best for machine learning beginners, machine learning experts, deep learning beginners and deep learning experts as well. All these courses are available online and you can excess through website or mobile app anywhere anytime. Go through the machine learning and deep learning course content comparison below and choose the one which best suited you. Our experts also mentioned best machine learning book, best machine learning YouTube videos, best deep learning book and best deep learning YouTube videos at the end of the post. Do not forget to look into it. Apart from the machine learning courses and deep learning tutorials, you may wanted to visit Best Google Golang Courses , Tutorials and Training for more expertise.

Best Machine Learning and Deep Learning Courses, Tutorials, Training and Certification

Machine Learning, Data Science and Deep Learning with Python

Machine Learning, Data Science and Deep Learning with PythonMachine Learning, Data Science and Deep Learning with Python course give you complete hands-on machine learning tutorial with Tensorflow, artificial intelligence, data science and neural networks. This is one of the best course to learn Machine learning with Python. If you are programmer and wanted to work in lucrative data science and machine learning domain then you will learn a lot from this course. You should have prior knowledge of scripting or python to take this course. This course taught by Frank Kane and till now 1 Lac+ students already enrolled in the course. Frank kane will make you master in build artificial neural networks with Tensorflow and Keras. You will be able to make predictions using linear regression, polynomial regression, and multivariate regression. Check complete list provided for Machine Learning Course by Udemy

Machine Learning, Data Science and Deep Learning with Python
Course type Paid
Duration 13 Hrs
Rating 4.5/5
Requirements Need to know basics scripting Python
Level Beginner
Students Enrolled 102000+
Language English
Subtitle Present
Subtitle Language English, Italian

Enroll the Course for Discounted Price

Key Features of Courses:

  • Course provides 101 lectures, 5 articles resource along with Full lifetime access, Certificate of Completion
  • Frank Kane covers the AI, machine learning, and data mining techniques real employers are looking
  • This course has covered most of machine lerning such as Deep Learning, Data Visualization, Transfer Learning, Sentiment analysis, Image recognition, Regression analysis, K-Means Clustering, Principal Component Analysis, Bayesian Methods, Decision Trees and Random Forests, Multiple Regression, Multi-Level Models, Support Vector Machines, K-Nearest Neighbor and many more
  • The course starts with a crash course of Python. So No need to worry much about python
  • Frank will teach you complete course based on his 9 years of experience at Amazon and IMDb
  • This course is one of the best deep learning course udemy, and best udemy machine learning

Course Contents:

  • Getting Started
  • Statistics and Probability Refresher, and Python Practise
  • Predictive Models
  • Machine Learning with Python
  • Recommender Systems
  • More Data Mining and Machine Learning Techniques
  • Dealing with Real-World Data
  • Apache Spark: Machine Learning on Big Data
  • Experimental Design / ML in the Real World
  • Deep Learning and Neural Networks
  • Final Project

Out Come of Course:
Software developers who wanted to change the domain in data science and machine learning career path will learn a lot from this course. You will be learning machine learning, AI, and data mining techniques. You can easily transit into the tech industry and can use this course to learn how to analyze data using code instead of tools.

I really liked the high-level overview. The material presented was “really a lot”, and I feel it just touched the surface. I think that this course can be easily broken down to more detailed couple of courses with more exercises like the “Final Project”. Frank, well-done; I hope that one day I will have the privilege of shaking hands with you.

Machine Learning by Coursera

coursera coursesMachine Learning by coursera is offered by Andrew Ng, who is the CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain. With this course you will be able to gain knowledge on effective machine learning techniques and practical exercise to implement them. After completion of this course you will be able to quickly and powerfully apply these techniques to new problems and get them to work for yourself. Machine learning course is provided by Stanford and you will get introduction to machine learning, datamining, and statistical pattern recognition. Here is the complete list of Machine Learning courses provided by Coursera

Machine Learning Coursera
Course type Enroll Free
Duration 56 Hrs
Rating 4.9/5
Requirements Basic Programming, nothing else
Level Beginner
Students Enrolled 2,513,476++
Language English
Subtitle Present
Subtitle Language Chinese, English, Hebrew, Spanish, Hindi, Japanese

Enroll the Course for Free

Key Features of Course:

  • You can Enroll for free in Machine Learning Course by Coursera
  • Flexible deadlines to complete the course
  • Introduction to datamining, machine-learning, statistical pattern recognition
  • Learn about clustering, dimensionality reduction, recommender systems, deep learning, parametric/non-parametric algorithms, support vector machine, kernel, neural networks
  • Learn to apply algorithms to build smart robots, computer vision, medical informatics, audio, text understanding, database mining
  • Gain theoretical and practical knowledge to apply these techniques to solve new problems
  • One of the best machine learning courses  Stanford Provided
  • More then 25 Lac students registered for this machine learning courses online
  • Coursera provides financial aid to learners who cannot afford the fee, So get machine learning tutorial for free.

Course Contents:

  • Introduction
  • Linear Regression with One Variable
  • Linear Algebra Review
  • Linear Regression with Multiple Variables
  • Octave/Matlab Tutorial
  • Logistic Regression
  • Regularization
  • Neural Networks: Representation
  • Neural Networks: Learning
  • Advice for Applying Machine Learning
  • Machine Learning System Design
  • Support Vector Machines
  • Unsupervised Learning
  • Dimensionality Reduction
  • Anomaly Detection
  • Recommender Systems
  • Large Scale Machine Learning
  • Application Example: Photo OCR

Out come of the Course:

You will have a better understanding datamining, machine-learning, statistical pattern recognition, clustering, dimensionality reduction, recommender systems, Deep learning, parametric/non-parametric algorithms, support vector machine, kernel, neural networks.

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Excellent starting course on machine learning. Beats any of the so called programming books on ML. Highly recommend this as a starting point for anyone wishing to be a ML programmer or data scientist.

NANODEGREE PROGRAM : Intro to Machine Learning

NANODEGREE PROGRAM Intro to Machine LearningThis Udacity Nanodegree Program of Intro to Machine Learning is created in association with Kaggle and AWS that will help you gain the fundamental skill sets required to be a data scientist/analysts. This is one of the machine learning tutorial with python language so course needs you to have knowledge of Python to go further with this course. The course can be tailored as per your learning speed and gives you a personalised mentor who helps you with your queries and keeps you motivated during the course.  You will get to know about foundational machine learning algorithms, starting with data cleaning and supervised models. Smoothly course will be move on to exploring deep and unsupervised learning. You will also get practical experience by applying your skills to code exercises and projects. Here is the list of Udacity Machine Learning Courses.

 

NANODEGREE PROGRAM : Intro to Machine Learning
Course type Paid
Duration 3 months, 10 hrs per week
Rating 4.8/5
Requirements Intermediate Python programming knowledge and basic knowledge of probability and statistics
Level Beginner
Students Enrolled NA
Language English
Subtitle NA
Subtitle Language NA

Enroll the Course with Discounted Price

Course Contents:

  • Project: Find Donors for CharityML
    • Regression
    • Perceptron Algorithms
    • Decision Trees
    • Naive Bayes
    • Support Vector Machines
    • Ensemble of Learners
    • Evaluation Metrics
    • Training and Tuning Models
  • Project: Create an Image Classifier
    • Introduction to Neural Networks
    • Implementing Gradient Descent
    • Training Neural Networks
    • Deep Learning with PyTorch
  • Project: Creating Customer Segments
    • Clustering
    • Hierarchical and Density-Based Clustering
    • Gaussian Mixture Models
    • Dimensionality Reduction

Key Features of Course:

  • Learn fundamentals of machine learning techniques such as data cleaning and supervised models.
  • Dig deeper into exploring Deep and unsupervises learning.
  • Learn to apply your knowledge to solve real-world projects from industry experts
  • Be in touch with knowledgeable mentors who will guide you with your learning and will keep you on track by motivating you and by answering your queries.
  • Flexibility in your learning program which helps you to learn at your own pace.
  • Get help in personal career coaching, interview preparations, resume service and linkedin profile review which will help to expand your career network
  • You will get 1 on 1 technical mentor for your technical problems
  • You will get Real world projects from industry experts
  • Nano degree program is as good as machine learning graduate programs and learn machine learning tutorial step by step

Outcome of the Course:
You will have foundational knowledge of machine learning techniques from data manipulation to supervised/unsupervised models and will get career advice from the mentors. You will learn machine learning techniques with a variety of real-world tasks, such as customer segmentation and image classification.

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Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z Hands-On Python & R In Data ScienceMachine Learning A-Z™: Hands-On Python & R In Data Science course is designed by Kirill Eremenko and Hadelin de Ponteves, two professional Data Scientists who wants to share their knowledge to help you understand and learn complex theory, algorithms and coding libraries in a simple way. The course is well organized to give a walk through to the world of Machine Learning. Already more than 461,173 students enrolled with this course and got benefited. With every module you will gain and develop new skills and get understanding of this sub-field of Data Science. You will be learning Machine Learning using Python and R language and also it is  adeep learning tutorial python, So you should know basics of Python and R. Check complete list provided for Machine Learning Course by Udemy.

Machine Learning A-Z™: Hands-On Python & R In Data Science
Course type Paid
Duration 41 Hrs
Rating 4.5/5
Requirements Basic High school mathematics
Level Beginner
Students Enrolled 461,173+
Language English
Subtitle Yes
Subtitle Language English, French, German, Indonesian, Italian, Japanese, Portuguese, Spanish, Turkish

Enroll Machine Learning Course in Discounted Price

Key Features of Course:

  • Learn about Data Processing, Deep Learning, Regression, Classification,  Clustering, Dimensionality Reduction, Reinforcement Learning, Natural Language Processing, Model Selection & Boosting and many more algorithms.
  • Various practical exercises and quizes based on real-life examples which will make you understand the depth of your learnings.
  • The course includes both Python and R code templates to help you with your own projects and can be downloaded from this course.
  • Best for all beginners as this course does not require any prior knowledge on Machine Learning.
  • Learn from 41 hours lecture, 31 articles and 5 downloadable resources
  • Course include 41 hours of Machine Learning and Deep learning videos, 31 Machine learning article and Deep learning article and 5 downloadable machine learning pdf resources and deep learning pdf resource also you will get certificate of completion

Course Contents:

  • Welcome to the course!
  • Part 1: Data Preprocessing
  • Part 2: Regression
  • Part 3: Classification
  • Part 4: Clustering
  • Part 5: Association Rule Learning
  • Part 6: Reinforcement Learning
  • Part 7: Natural Language Processing
  • Part 8: Deep Learning
  • Part 9: Dimensionality Reduction
  • Part 10: Model Selection & Boosting
  • Bonus Lectures

Outcome of the Course:
Learn and start a career in Data Science. After this course you will be able to add value to your job, business by using powerful Machine Learning tools. Course has some hand-on practises to building your own models.

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Deep Learning Specialization by Coursera

Deep Learning Specialization course is prepared for you by Andrew Ng (CEO/Founder Landing AI), Kian Katanforoosh (Lecturer of Computer Science at Stanford University) and Younes Bensouda Mourri (Mathematical & Computational Sciences, Stanford University). This course focuses on Deep learning which is one of the most highly seeked skill. After completion of this course you will have a good understanding of Deep learning. The instructors have divided this course in 5 parts and will teach you about foundation of Deep learning, how to build neural networks and how to build machine learning projects. This course was offered by deeplearning.ai and it is Intermediate Level course. Here is the complete list of Machine Learning courses and Deep learning provided by Coursera.

Deep Learning Specialization Course
Course type Enroll Free
Duration 3 months, 11 hours per week
Rating 4.9/5
Requirements Basic Programming in any domain
Level Intermediate
Students Enrolled 240,192+
Language English
Subtitle Yes
Subtitle Language English, Chinese (Traditional), Arabic, French, Ukrainian, Chinese(Simplified), Portuguese (Brazilian), Korean, Turkish, Spanish, Japanese

Enroll the Course for Free

Key Features of Course:

  • Enroll for free in coursera course Deep Learning Specializatio
  • You will Get the certification on completion
  • Flexible deadlines to complete the course
  • Learn the basics of deep learning
  • Understand to build neural networks and lead successful machine learning projects
  • Learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization etc
  • Work on multiple real time case studies from autonomous driving, healthcare, music generation, natural language processing, sign language reading
  • Get theoretical as well as practical knowledge which gets applied in industry.
  • Practice all these case studies in Python and TensorFlow

Course Contents:

  • Introduction to deep learning
  • Neural Networks Basics
  • Shallow neural networks
  • Deep Neural Networks

Outcome of Course:
You will master Deep Learning, Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, autonomous driving, healthcare, music generation, natural language processing, sign language reading and understand how to apply it, and build a career in AI.

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HarvardX’s Data Science Professional Certificate by Edx

HarvardX’s Data Science Professional Certificate by EdxThis HarvardX Data Science program provides useful and necessary skills and knowledge to deal with rela world data analysis challenges. This program uses the R software environment. You will a detailed knowledge on differnet modules and concepts such as probability, inference, regression, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document reparation with RStudio. You will be able to learn statistical concepts and data analysis techniques simultaneously. You will be provided with multiple case studies like Trends in World health and Economics, US crime rates, The Financial Crisis of 2007-08, Election Forecasting, Building a Baseball Team, and Movie Recommendation Systems.

HarvardX’s Data Science Professional Certificate
Course type Paid
Duration 2-4 Months
Rating 4.7/5
Requirements Basic Programming in any domain
Level Intermediate
Students Enrolled NA
Language English
Subtitle NA
Subtitle Language NA

Enroll the Course for Free

Key Features of Course:

  • Experts from HarvardX teaching you online learning of Data Science
  • Learn about fundamentals of R programming skills
  • Learn and explore statistical concepts such as probability, inference, and modeling and apply them in practice.
  • Gain a good experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr.
  • Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio.
  • Implement variouse machine learning algorithms and gain in-depth knowledge of this area with real-life case studies.

Course Contents:

  • Data Science: R Basics
  • Data Science: Visualization
  • Data Science: Probability
  • Data Science: Inference and Modeling
  • Data Science: Productivity Tools
  • Data Science: Wrangling
  • Data Science: Linear Regression
  • Data Science: Machine Learning
  • Data Science: Capstone

Outcome of Course:
Gain knowledge in data-science and machine-learning and start a career in that field along with that mastering in R Programming Language.

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Hands-on artificial intelligence by Edx

Hands-on artificial intelligence by EdxIBM has brought this certification to help you explore the details of deep learning. This course includes the fundamentals of Deep learning including various Neural Networks for supervised and unsupervised learning. During this course you will be able build models and algorithms using different libraries such as PyTorch, TensorFlow and Keras. As part of the course you will be working on various assignments and real-world projects.

Hands-on artificial intelligence
Course type Paid
Duration 2-4 Months
Rating 4.6/5
Requirements Basic Programming in any domain
Level Intermediate
Students Enrolled NA
Language English
Subtitle NA
Subtitle Language NA

Enroll the Course for Free

Key Features of Course:

  • Learn fundamental concepts of Deep Learning along with various Neural Networks for supervised and unsupervised learning.
  • Learn use of popular Deep Learning libraries such as PyTorch, TensorFlow and Keras which can be applied to industry problems.
  • Build, train, and deploy different types of Deep Architectures, including Convolutional, Recurrent Networks, and Autoencoders.
  • Understand application of Deep Learning to real-world scenarios such as Computer Vision and object recognition, image and video processing,
  • Natural Language Processing, text analytics, recommender systems, and other types of classifiers.
  • Get expertise in Deep Learning at scale with GPU accelerated hardware.

Course Contents:

  • Deep Learning Fundamentals with Keras
  • Deep Learning with Python and PyTorch
  • Deep Learning with Tensorflow
  • Using GPUs to Scale and Speed-up Deep Learning
  • Applied Deep Learning Capstone Project

Outcome of Course:
Get mastery in Deep Learning and as part of course work on capstone project that can be showcased in your resume

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Machine Learning Certification Course

Simplilearn-free-courses-tutorial-certificateMachine Learning Certification Course offers an in-depth learning of Machine Learning topics with developing algorithms, regression, handling real time data, classification, time series modeling and Bagging techniques along with Deep Learning fundamentals and many more. You will be learning how to use best way to use Python in Machine learning and Data Mining. Simplilearn will referesh your Math and Statistics. There are multiple registration option available such as self paced learning and blended learning. You can opt based on your need.

Machine Learning Certification Course
Course type Paid
Duration 44 Hrs
Rating 4/5
Requirements Basic Python Programming
Level Basic
Students Enrolled 4232
Language English
Subtitle NA
Subtitle Language NA

Enroll the Course for Free

Key Features of Course:

  • You will Gain expertise with 25+ hands-on exercises along with 4 real-life industry projects
  • You will get mentoring sessions from industry experts
  • Best part is you will get 44 hours of instructor-led training with certification
  • You will be learning machine learning topics Supervised and unsupervised learning, Time series modeling, Linear and logistic regression, Kernel SVM, Decision trees, K-Means clustering, Naive Bayes, Decision tree, Random forest classifiers, Boosting and Bagging techniques along with Deep Learning fundamentals
  • You will have free access of Data Science with Python, Math Refresher and Statistics Essential for Data Science
  • You will be awarded by industry-recognized course completion certificate

Course Contents:

  • Course Introduction
  • Introduction to AI and Machine Learning
  • Data Preprocessing
  • Supervised Learning
  • Feature Engineering
  • Supervised Learning Classification
  • Unsupervised Learning
  • Time Series Modeling
  • Ensemble Learning
  • Recommender Systems
  • Text Mining
  • Project Highlights
  • Practice Projects

Outcome of the Courses:
You will be certified Machine Learning practitioner with 4 real-life industry projects. Also learn how to use Python in this Machine Learning training course.

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Machine Learning and Practical Deep Learning by fast.ai

fast ai machine learning deep learningMachine Learning and Practical Deep Learning by fast.ai are making deep learning easier to use and getting more people from all backgrounds. Unlikely your background, fast.ai will make your involvement in Artificial Intelligence, Machine learning and Deep Learning. Introduction to Machine Learning for Coders! taught by Jeremy Howard. Jeremy is founder of Enlitic and will teach you machine learning model with how to create machine learning model from scratch, data preparation, model validation, and building data products. Best part is course is based on University of San Francisco for the Masters of Science in Data Science program.

Machine Learning and Deep Learning by Fast.ai
Course type Free
Duration 40-60 Hrs
Rating 4.6/5
Requirements Basic Python Programming
Level Basic
Students Enrolled NA
Language English
Subtitle NA
Subtitle Language NA

 

Key Features of Course:

  • The complete course is free of cost without ads, It is self paced learning program
  • Learn Deep Learning step by step guide and with problem solving hand-on
  • Access to fast.ai for latest update and news related to the domain
  • Course is recorded at the University of San Francisco for the Masters of Science in Data Science program
  • Ask and Answer questions on the forums where most discussion happen
  • Solve challenging end-to-end problems such as natural language translation

Course Contents for Machine Learning

  • Introduction to Random Forests
  • Random Forest Deep Dive
  • Performance, Validation and Model Interpretation
  • Feature Importance, Tree Interpreter
  • Extrapolation and RF from Scratch
  • Data Products and Live Coding
  • RF from Scratch and Gradient Descent
  • Gradient Descent and Logistic Regression
  • Regularization, Learning Rates and NLP
  • More NLP and Columnar Data
  • Embeddings
  • Complete Rossmann, Ethical Issues

Enroll Machine Learning Course for Free

Course Content for Deep Learning

  • Image recognition
  • CNNs
  • Overfitting
  • Embeddings
  • NLP
  • RNNs
  • CNN Architectures
  • Object detection
  • Single shot multibox detector (SSD)
  • NLP classification and transfer learning
  • Neural translation; Multi-modal learning
  • Generative Adversarial Networks
  • CycleGANs; Data ethics; Style transfer
  • Super resolution; Segmentation with Unets

Enroll Deep Learning Course for Free

Outcome of the Courses:

You will be learning Machine Learning, Artificial Intelligence and Deep Learning for free of cost with world class university classroom.

 

 

Introduction to Machine Learning with R

Introduction to Machine Learning with RIntroduction to Machine Learning with R will provide you best hands on with good amount of exercises. These exercise will make you perfect in machine learning topics viz performance measures, classification, Regression and Clustering and many more. You will be able to gain more insight into the assessment and training of different machine learning models. Best part is you can enroll to the course for free.  You may wanted to checkout other Machine Learning Course from Datacamp.

Introduction to Machine Learning with R
Course type Enroll Free
Duration 6 Hrs
Rating 4.5/5
Requirements Basic R Programming
Level Intermediate
Students Enrolled 83,386
Language English
Subtitle NA
Subtitle Language NA

Enroll to Course for Free

Key Features of Course:

  • You can enroll to the course for Free
  • You will learn major XP of Machine Learning such as Performance measures, Classification, Regression, Clustering
  • You will have ultimate Hands-on with 81 Exercises
  • Course include 15 Videos of 6 Hours traning along with Course Completion certificate
  • You will learn to assess the performance of both supervised and unsupervised learning algorithms

Course Contents:

  • What is Machine Learning
  • Performance measures
  • Classification
  • Regression
  • Clustering

Outcome Of Courses:
You will have complete picture of Machine Learning with R language and have idea of Performance measures, Classification, Regression, Clustering

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Deep Learning Course with TensorFlow

Simplilearn-free-courses-tutorial-certificateDeep Learning is one of the segments of Artificial Intelligence and machine learning technologies. Deep Learning Course with TensorFlow will help you to become master in deep learning techniques and build deep learning models using TensorFlow, TensorFlow is open-source software library developed by Google for research in machine learning and deep neural networks. You will get hand-on in Deep Learning application such as Image Processing, Natural Language Processing, Speech Recognition, Video Analytics. This course is designed with IBM.

Deep Learning Course with TensorFlow
Course type Paid
Duration 40 Hrs
Rating 3.9/5
Requirements Basic Programming Knowledge
Level Intermediate
Students Enrolled 1991
Language English
Subtitle NA
Subtitle Language NA

Enroll to Course for Free

Key Feature of Course:

  • You will get 40 hours of instructor-led training of Deep Learning along with 24*7 support with dedicated project mentoring sessions
  • You will get hand-on of Real-life industry based projects
  • Simlilearn provides you 7 Days Money back Guarantee
  • Get Free course contents of Math Refresher and Deep Learning Fundamentals
  • Get industry recognise certificate after completion of course and exam

Course Contents:

  • Introduction to TensorFlow
  • Perceptrons
  • Activation Functions
  • Artificial Neural Networks
  • Gradient Descent and Back propagation
  • Optimization and Regularization
  • Intro to Convolutional Neural Networks
  • Introduction to Recurrent Neural Networks
  • Deep Learning applications

Outcome of Course:
You will be able to Understand the concepts of TensorFlow at end of Course and able to implement deep learning algorithms, understand neural networks. Also you will understand the language and fundamental concepts of artificial neural networks. You will be able to Differentiate between machine learning, deep learning and artificial intelligence.

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