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I tried the new AI tool for Logseq, and the result seems promising! Of course, GPT-3 won't magically make you smarter, but it does save you some time and helps you write more.

We're now seeing more and more AI writing tools like LEX and Jasper, but are there going to be more AI note-taking tools too?

Mentioned Tools:
LEX: https://lex.page/
Jasper: https://www.jasper.ai/
Napkin: https://napkin.one/?via=shu
Mem: https://get.mem.ai/
Logseq: https://logseq.com/
OpenAI: https://openai.com/api/


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Recently, I have trained GPT-2 on the Lakh MIDI dataset. It is a collection of roundabout 175K MIDI files. Training takes quite a long time! But using NVIDIA DGX-2 really made a difference!

The unprocessed Lakh MIDI dataset:
https://colinraffel.com/projects/lmd/

Checkout NVIDIA DGX-2:
https://www.nvidia.com/en-us/data-center/dgx-2/

Checkout the NVIDIA DGX Systems family:
https://www.nvidia.com/en-us/d....ata-center/dgx-syste


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This AWS tutorial for beginners will help you understand what is AWS (Amazon Web Services), how did AWS become so successful, the services that AWS provides (AWS EC2, Amazon Elastic Beanstalk, Amazon Lightsail, Amazon Lambda, Amazon S3, Amazon redshift, amazon ECS, amazon route 53, amazon vpc, AWS CloudFront, AWS sagemaker, AWS autoscaling, and AWS elastic beanstalk), the future of AWS and a demonstration on deploying, in the end, we’ll also be discussing AWS certification and AWS interview questions for beginners and advanced level. This AWS tutorial video is suitable for those individuals who aspire to become AWS Certified Solution Architects. However, let move ahead and understand what AWS actually is and what are the services that AWS provides to an organization.

The below topics are covered in this AWS tutorial:
What is AWS?
AWS Tutorial
AWS EC2
AWS Lambda
AWS S3
AWS IAM
AWS cloud formation
AWS ECS
AWS route 53
AWS Elastic beanstalk
AWS VPC
AWS SageMaker
AWS CloudFront
AWS Autoscaling
0AWS Redshift
AWS vs Azure
AWS vs GCP
AWS vs Azure vs GCP
Kubernetes on AWS
How to become a solution architect
AWS Interview questions -Part 1
AWS Interview questions -Part 2

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What is AWS?
Amazon web service is an online platform that provides scalable and cost-effective cloud computing solutions. AWS is a broadly adopted cloud platform that offers several on-demand operations like compute power, database storage, content delivery, etc., to help corporates scale and grow.

AWS Services
Amazon has many services for cloud applications. Let us list down a few key services of the AWS ecosystem and a brief description of how developers use them in their business.
Amazon has a list of services:
✅Compute service
✅Storage
✅Database
✅Networking and delivery of content
✅Security tools
✅Developer tools
✅Management tools

About AWS Solutions Architect Certification Training Course:
AWS certification training is essential for every aspiring AWS certified solutions architect. You will master AWS architectural principles and services such as IAM, VPC, EC2, EBS and elevate your career to the cloud, and beyond with this AWS solutions architect course. The AWS Solutions Architect Certification training will enable you to design, plan and scale AWS implementations utilizing over 70 cloud computing services. The AWS course is aligned with the latest AWS exam featuring Amazon designated best practices.

What does an AWS solutions architect do?
An AWS solutions architect is a professional who designs cost-effective, available, scalable, and fault-tolerant systems on AWS. They identify and define the technical requirements for an AWS-based application and decide which AWS services meet those requirements. They have a clear understanding of the basic architectural principles of building on the AWS Cloud platform.

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This Edureka "Neural Network Tutorial" video (Blog: https://goo.gl/4zxMfU) will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail.
Topics Covered:
00:00:00 Introduction
00:00:42 Agenda
00:01:02 Why Neural Networks
00:02:24 Motivation behind Neural Networks
00:04:46 What are Neural Networks
00:06:41 How it Works
00:11:54 Modes in perceptron
00:13:55 Activation Function
00:16:37 Assign Weights
00:20:10 Example of Artificial Neural Networks
00:24:47 Hands On

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This Deep Learning full course covers all the concepts and techniques that will help you become an expert in Deep Learning. First, you will learn the basics of Deep Learning and understand how to install TensorFlow, what TensorFlow is, TensorFlow Object detection API works, different Deep Learning frameworks, convolutional neural networks, recurrent neural networks in Python, Deep Learning applications, and look at the essential interview questions.

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Dataset link - https://drive.google.com/drive..../folders/1COH2WuRtru

Below topics are explained in this Deep Learning full course video:
1. Deep Learning
2. Working of neural networks
3. Horus Technology
4. What is Deep Learning?
5. Image Recognition
6. Why do we need Deep Learning?
7. Applications of Deep Learning
8. What is a Neural Network?
9. Biological Neuron vs Artificial Neuron
10. Why are Deep Neural Nets hard to train?
11. Neural Network Prediction
12. Top Deep Learning Libraries
13. Why TensorFlow?
14. What is TensorFlow?
15. What are Tensors?
16. What is a Data Flow graph?
17. Program Elements in TensorFlow
18.TensorFlow program basics
19. Use case Implementation using TensorFlow
20.TensorFlow Object Detection
21. COCO Dataset
22.TensorFlow Object Detection API Tutorial
23. Deep Learning Frameworks
24. Keras
25.PyTorch
26. How image recognition works?
27. How does CNN recognizes images?
28. Types of Recurrent Neural Network
29. Working of LSTMs
30. Deep Learning Applications


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Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you'll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks, and traverse layers of data abstraction to understand the power of data and prepare you for your new role as a deep learning scientist.

You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:

1. Understand the concepts of TensorFlow, its main functions, operations, and the execution pipeline
2. Implement deep learning algorithms, understand neural networks, and traverse the layers of data abstraction, which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks, and high-level interfaces

Learn more at:
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The Scrum Master role is a special role for an Agile Team member who spends much of her time helping other team members communicate, coordinate, and cooperate; generally, this person assists the team in meeting their delivery goals.

➡️ About Certified ScrumMaster® (CSM) Certification Training Course

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React: Use Array.map() to Dynamically Render Elements
#100DaysOfCode

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In this full course video on Big data, you will learn about Big data, Hadoop, and Spark. First, we will look into a big data tutorial, the challenges in big data, and how Hadoop solves these challenges. You will learn how to install Hadoop, then understand the various components of Hadoop that are HDFS, MapReduce, and YARN. HDFS will teach you how to store big data, and MapReduce will show you how to process this big data. In YARN, you will learn how cluster resource management works. In addition to these components, you will also look into the Hadoop ecosystem, which consists of Hive, Pig, Sqoop, and HBase.

The below topics are explained in this Big Data full course video:
1. Evolution of Big Data
2. Why Big Data?
3. What is Big Data?
4. 5 V's of Big Data
5. Challenges of Big Data
6. Hadoop as a Solution
7. Cloudera Hadoop Installation
8. Hadoop Ecosystem
9. Hadoop Distributed File System
10. MapReduce Analogy
11. What is MapReduce?
12. Parallel Processing-MapReduce
13. MapReduce Workflow
14. MapReduce Architecture
15. Hadoop 1.0(MR 1)
16. Limitations of Hadoop 1.0(MR 1)
17. Need for YARN
18. What is YARN?
19. YARN Components
20. YARN Components-Node MAnager
21. What is Sqoop?
22. Sqoop Features
23. Sqoop Architecture
24. What is Apache Spark?
25. History of Apache Spark
26. Apache Spark Installation on Windows
27. Apache Spark Installation on Ubuntu
28. YARN

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This Data Engineering course is ideal for professionals, covering critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. This program is delivered via live sessions, industry projects, IBM hackathons, and Ask Me Anything sessions.
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AWS DevOps Roadmap 2024 by simplilearn is dedicated to help aspiring AWS DEvOps Engineers to learn the DevOps and AWS Fundmaentals and also the AWS DevOps Learning Path 2024. DevOps Careers will be one of the highest in the year 2024 and ahead. So. This Simplilearn video focuses on enlightening the perfect road map to become a professional AWS DevOps Engineer.

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Jimmy Apples (who previously leaked a supposed AGI) was proven right again. OpenAI began work on Arrakis alongside GPT-4, its latest AI model, to create a system that could power AI applications like ChatGPT much more cheaply, the Information report said. The company ended up scrapping it earlier this year after it struggled to meet expectations around efficiency, the report added.
AI models that enable applications like ChatGPT are expensive and resource-intensive, requiring expensive compute power from cloud providers such as Microsoft, Amazon, and Google. Estimates have suggested that ChatGPT costs more than $700,000 per day to run.
OpenAI struck a partnership with Microsoft in January, giving it access to the tech giant's Azure platform. The Information reported that "some executives at Microsoft" were left disappointed by the shortcomings of Arrakis.
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Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity.
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TIMESTAMPS:
00:00 Jimmy Apple's New OpenAI Leaks
01:04 All New OpenAI Leaks
04:08 What is Artificial General Intelligence
05:58 Future of OpenAI
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#openai #ai #leaks

Discover strange new universes that turn up at the core of Einstein’s General Relativity. Head to https://brilliant.org/veritasium to start your free 30-day trial, and the first 200 people get 20% off an annual premium subscription.

If you’re looking for a molecular modeling kit, try Snatoms – a kit I invented where the atoms snap together magnetically – https://ve42.co/SnatomsV

▀▀▀
A massive thank you to Prof. Alex Kontorovich for all his help with this video.

A huge thank you to Prof. Geraint Lewis and Dr. Ashmeet Singh for helping us understand the applications of Non-Euclidean geometry in astronomy/cosmology.

Lastly, a big thank you to Dr. Henry Segerman and Dr. Rémi Coulon for helping us visualize what it’s like to be inside hyperbolic space and helping us understand hyperbolic geometry.

▀▀▀
Images:
Euclid via Science Museum Group - https://ve42.co/Euclid

Geodesy survey via ams - https://ve42.co/Geodesy

John Wheeler via NAS Online - https://ve42.co/Wheeler

▀▀▀
References:
Dunham, W. (1991). Journey through Genius: Great Theorems of Mathematics. John Wiley & Sons.

Bonola, R. (1955). Non-Euclidean geometry: A critical and historical study of its development. Courier Corporation.

Library of Congress. (n.d.). The Library of Congress. - https://ve42.co/LibofCongress

Euclid’s Elements, Wikipedia - https://ve42.co/Elements

The History of Non-Euclidean Geometry, Extra History via YouTube - https://ve42.co/ExtraHistory

We (could) live on a 4D Pringle - Physics for the Birds via YouTube - https://ve42.co/4DPringle

Parallel Postulate, Wikipedia - https://ve42.co/Parallel

Prékopa, A., & Molnár, E. (Eds.). (2006). Non-euclidean geometries: János Bolyai memorial volume (Vol. 581). Springer Science & Business Media.

St Andrews, University of. (n.d.). Bolyai. MacTutor History of Mathematics. - https://ve42.co/Bolyai

Bolyai, J. (1896). The Science Absolute of Space.. (Vol. 3). The Neomon.

Gauss, Wikipedia - https://ve42.co/Gauss

Singh, U. (2022). Gauss-Bolyai-Lobachevsky: The dawn of non-euclidean geometry. Medium. - https://ve42.co/CPNonEuclidean

Landvermessung, D. Z. (1929). Abhandlungen ueber Gauss' wissenschaftliche Taetigkeit auf den Gebieten der Geodaesie, Physik und Astronomie Bd. 11, Abt. - https://ve42.co/Landvermessung

Nikolai Lobachevsky, Wikipedia - https://ve42.co/Lobachevsky

Lobachevskiĭ, N. I. (1891). Geometrical researches on the theory of parallels. University of Texas.

A Problem with the Parallel Postulate, Numberphile via YouTube - https://ve42.co/NumberphileParallel

Riemann, B. (2016). On the hypotheses which lie at the bases of geometry. Birkhäuser. - https://ve42.co/Riemann

Einstein, A. (1905). On the electrodynamics of moving bodies. Annalen der physik, 17(10), 891-921. - https://ve42.co/Einstein1905

ESA/Hubble. (n.d.). Hubblecast 90: The final frontier of the Frontier Fields. ESA/Hubble. - https://ve42.co/Einstein1905

Agazie, G., et al. (2023). The NANOGrav 15 yr data set: Constraints on supermassive black hole binaries from the gravitational-wave background. - https://ve42.co/NANOGrav

Secrets of the Cosmic Microwave Background, PBS Spacetime via YouTube - https://ve42.co/PBSCMB

Wood, C. (2020). How Ancient Light Reveals the Universe's Contents. Quanta Magazine. - https://ve42.co/AncientLight

Collaboration (2014). Planck 2013 results. XVI. Cosmological parameters. A&A, 571, A16. - https://ve42.co/Planck2013

WMAP Science Team, NASA. (2014). Matter in the Universe. WMAP, NASA. - https://ve42.co/WMAP2014

What Is The Shape of Space, minutephysics via YouTube - https://ve42.co/SpaceShape

Shape of the universe, Wikipedia - https://ve42.co/UniverseShape

Crocheting Hyperbolic Planes: Daina Taimina by Ted, via YouTube - https://ve42.co/Hyperbolic

Hyperbolic Crochet model - https://ve42.co/Crochet

▀▀▀
Special thanks to our Patreon supporters:
Adam Foreman, Amadeo Bee, Anton Ragin, Balkrishna Heroor, Bernard McGee, Bill Linder, Burt Humburg, Dave Kircher, Diffbot, Evgeny Skvortsov, Gnare, Jesse Brandsoy, John H. Austin, Jr., john kiehl, Josh Hibschman, Juan Benet, KeyWestr, Lee Redden, Marinus Kuivenhoven, Mario Bottion, Max Maladino, Meekay, meg noah, Michael Krugman, Paul Peijzel, Richard Sundvall, Sam Lutfi, Stephen Wilcox, Tj Steyn, TTST, Ubiquity Ventures

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Directed by Casper Mebius
Written by Casper Mebius, Petr Lebedev, Emily Zhang, Derek Muller, and Alex Kontorovich
Edited by Jack Saxon
Animated by Fabio Albertelli, Ivy Tello, and Mike Radjabov
Illustrations by Jakub Misiek and Celia Bode
Filmed by Derek Muller
Produced by Casper Mebius, Derek Muller, and Han Evans

Additional video/photos supplied by Getty Images, Pond5, and by courtesy of: NASA, NASA's Goddard Space Flight Center, NASA Goddard Flight Lab/ CI Lab, NASA’s WMAP science teams, ESO, and ESA/Hubble.
Music from Epidemic Sound
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In this exclusive How To Use DALL E Image Generator video, we're peeling back the layers of DALL-E, OpenAI's revolutionary image generation tool, in a way that's both informative and engaging for tech enthusiasts. We're not just skimming the surface; we delve deep into the mechanics and algorithms that make DALL-E a game-changer in AI-driven art. This isn't your typical tutorial. We're offering a unique blend of technical insights and practical advice, tailored for those who love to explore the intersection of technology and creativity. Discover how to transform your abstract ideas into vivid images with DALL-E's advanced capabilities

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1:08 - Microsoft Excel Overview
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8:02 - Saving an Excel file
10:31- Excel Customization
13:21- Important areas of working
15:51- What is formula bar
19:18- ribbons
24:06- Formatting excel and shortcuts
33:04- Basic Formulas
50:00- Find and Replace
1:05:49- Text Functions-Formatting Data
1:39:25- count functions
1:40:45- Relative Reference
1:57:17- Absolute Reference
2:14:12- Mixed Reference
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9:17:14- Using Macro Recorder
9:39:12- Recap
9:51:18- Variable, data types and constants
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10:21:11- Constants

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Siempre quise saber por qué las películas de cine se veían mejor que las de video. Las imágenes electrónicas en movimiento tienen una larga historia, pero fueron inventadas con un propósito diferente. 📺 SUSCRÍBETE para ver todos nuestros videos:http://bit.ly/Suscribirse_Veritasium_en_español

Quiénes de ustedes se han criado viendo un tubo de rayos de catódicos. Los televisores eran aparatos que podían llegar a ser muy grandes y pesados. Pero la tecnología avanzó y cada vez es más difícil encontrarlos.

Este es un video que he querido hacer desde hace mucho tiempo, sobre qué hace que un video se vea como un video y, hasta hace 10 años más o menos, no se veía tan atractivo como las películas de cine. Crecí con las dos tecnologías en paralelo (cintas de cine y de video) y siempre me parecieron dos formas de lograr los mismos fines: grabar y reproducir imágenes en movimiento.
Pero sus historias son bastante distintas. El cine siempre fue una forma de capturar imágenes en movimiento para su posterior reproducción.
El video comenzó como una forma de transferir imágenes de un lugar a otro instantáneamente. Esto se remonta a la primera máquina de fax, la televisión mecánica, la televisión en directo y, finalmente, las cintas de video.
Esta historia se centra en las primeras décadas del vídeo y no en los más recientes cambios a las cámaras de chip y el almacenamiento en estado sólido. Tal vez esa sea una historia para otro día.

Muchas gracias a:

Richard Diehl, Video Labguy https://www.youtube.com/user/videolabguy
https://www.labguysworld.com

Branch Education por sus animaciones impresionantes
https://ve42.co/BranchEd

Minutephysics por las animaciones de la TV mecánica
https://www.youtube.com/minutephysics

Mark Schubin
Ingeniero y divulgador, becario de por vida del SMPTE
https://www.smpte.org


Fuentes y referencias adicionales:

The Dawn of Tape: Transmission Device as Preservation Medium
https://ve42.co/dawnoftape

What Sparked Video Research in 1877? The Overlooked Role of the Siemens Artificial Eye
https://ve42.co/sparkvideo

Video Preservation Website:
https://cool.culturalheritage.....org/videopreservatio
Image Orthicon Tube:
http://interiorcommunicationse....lectrician.tpub.com/
Film vs Digital
https://stephenfollows.com/film-vs-digital/
Eyes of a Generation:
http://eyesofageneration.com

Television in the US:
https://www.youtube.com/redirect?event=video_description&v=rjDX5ItsOnQ&redir_token=659XFg6LdOuhcg9MgOOwI7cHP3d8MTU5MDAwODI5MkAxNTg5OTIxODky&q=http%3A%2F%2Fwww3.northern.edu%2Fwild%2Fth100%2Ftv.htm
http://www.classictvinfo.com

Música de https://www.epidemicsound.com "Seaweed" "Capture a Picture 1" "Colorful Animation 4"

Video en Inglés del Canal @veritasium :
https://www.youtube.com/watch?v=rjDX5ItsOnQ
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🕹 Este canal de Youtube es administrado por: https://www.unilingo.tv/
❓Comentarios o sugerencias de traducción: [email protected]
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#veritasiumenespañol

Want to know how creative web applications are developed? Our video about Streamlit will help you to know about the same.

This video about Streamlit Tutorial by Intellipaat will take a deep dive into What is Streamlit. Furthermore, it will explore more about its uses and Installation, and not only this but will also help you to understand the basic functions of Streamlit, Input widgets, and will end with its Practical Implementation.

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2:50 - Installation
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5:22 - Input Widgets
6:00 - Practical Implementation

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🔥SQL Certification Course : https://www.simplilearn.com/sql?utm_campaign=23May2024WhatIsDBMS&utm_medium=DescriptionFF&utm_source=youtube
🔥IIT Kanpur Professional Certificate Course In Data Analytics (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=23May2024WhatIsDBMS&utm_medium=DescriptionFF&utm_source=youtube
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Dive into the world of Database Management Systems (DBMS) with this easy-to-follow Introduction To DBMS tutorial! We'll explain what DBMS is and why it's important. Learn about different types of databases like Relational, NoSQL, Object-oriented, Hierarchical, and Network databases. Each type has unique features that make them useful for different tasks. We'll also cover basic DBMS concepts such as tables, rows, and columns, primary and foreign keys, and how indexes and queries work. Plus, find out about future trends like Big Data, distributed and cloud databases, and how machine learning is changing the way we manage data. This video uses simple language and clear visuals to make complex ideas easy to understand. Whether you're new to databases or just want to learn more, this tutorial is perfect for you. Watch now and start your journey to mastering DBMS!

In this Introduction To DBMS video, we cover the following topics:

00:00:06 Introduction
00:00:29 Introduction to Databases
00:01:58 What is DBMS?
00:03:28 Components of DBMS
00:04:55 Functions of DBMS
00:05:43 Advantages of Using DBMS
00:06:56 Types of DBMS
00:09:25 Common Use Cases of DBMS
00:11:09 Future Trends in DBMS

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#SQL #DBMS #DatabaseManagementSystem #2024 #simplilearn

➡️ About SQL Certification Course
This SQL certification course gives you all of the information you need to successfully start working with SQL databases and make use of the database in your applications. Learn how to correctly structure your database, author efficient SQL statements and clauses, and manage your SQL database for scalable growth.

✅ Key Features
Covers basic to advanced SQL concepts
Dedicated live sessions by faculty of industry experts
Self-paced learning modules to learn at your own pace
Hands-on projects for real-world application
Engaging learning experience featuring demo sessions and real-world examples
Industry-recognized certificate upon completion

✅ Skills Covered

- SQL
- Database Management System DBMS
- RealWorld Problem Solving
- MySQL
- Data Analysis

Learn More:- 🔥SQL Certification Course : https://www.simplilearn.com/sql?utm_campaign=23May2024WhatIsDBMS&utm_medium=Description&utm_source=youtube

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( Data Science Training: https://www.edureka.co/data-sc....ience-r-programming- )
This "Machine Learning with R" video by Edureka will help you to understand the core concepts of Machine Learning followed by a very interesting case study on Pokemon Dataset in R. This tutorial will comprise of these topics:

1. Understanding Machine Learning
2. Applications of Machine Learning
3. Types of Machine Learning Algorithms
4. Case Study on the "Pokemon Dataset" to implement Machine Learning Algorithms

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Check our complete Data Science playlist here: https://goo.gl/60NJJS

#LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience

How it Works?
1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

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About the Course

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

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Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

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Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).

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Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "

🔥Edureka Tensorflow Training: https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka LSTM Explained video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs.
00:00 Introduction
00:36 Agenda
00:47 Introduction to NLP
01:46 Ways to Process Text Data
02:57 Recurrent Neural Networks
22:02 Long Short-term Memory
51:46 LSTM Use Cases
53:45 Real Time Applications of LSTM

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🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s

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#Edureka #DeepLearningEdureka #LSTMExplained #NeuralNetworks #DeepLearningTraining #DeepearningTutorial #EdurekaTraining

How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course
Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. 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, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.


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Who should go for this course?

The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'

2. Analytics Managers who are leading a team of analysts

3. Business Analysts who want to understand Deep Learning (ML) Techniques

4. Information Architects who want to gain expertise in Predictive Analytics

5. Professionals who want to captivate and analyze Big Data

6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

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Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.


For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).

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