In this first video of this series in object detection we try to understand what object detection is and how it works. We also look at an overview of model architectures in object detection such as a sliding windows approach, regional based family of models (r-CNN) and lastly a quick overview of Yolo which we will go into more in depth (and code from scratch) in a future video!

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Object Detection Playlist:
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PyTorch Playlist:
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A gentle intro to neural networks.

Perceptron Video : https://www.youtube.com/watch?v=4Gac5I64LM4

Logistic Regression Video : https://www.youtube.com/watch?v=9zw76PT3tzs

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐲𝐛𝐞𝐫 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 : https://www.edureka.co/cyberse....curity-certification 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka video on "Cybersecurity Certifications" talks about some of the major cybersecurity certifications required to get into the security industry. If you're interested in a developing an exciting career in cyber security, check out 2023s top ten cybersecurity certifications.
00:00:00 Introduction
00:00:59 Cybersecurity Certifications: Know the Basics
00:02:29 Category of Certification Programs
00:03:02 Certifications in IT Security
00:04:19 CompTIA Security+ Certification
00:05:15 CompTIA Security+: Domains
00:05:40 GSEC: GIAC Security Essentials Certification
00:06:39 GSEC: Domains
00:06:59 SSCP: Systems Security Certified Practitioner
00:07:39 SSCP: Domains
00:08:26 CEH: Certified Ethical Hacker
00:09:26 CEH: Domains
00:09:47 CISA: Certified Information Systems Auditor
00:10:32 CISA: Domains
00:10:43 CISM: Certified Information Security Manager
00:11:32 CISM: Domains
00:11:50 CRISC: Certified in Risk and Information System Control
00:12:29 CRISC: Domains
00:12:41 CISSP: Certified Information System Security Professional
00:13:58 CISSP: Domains
00::14:18 How To Choose the Right Cybersecurity Certification?

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Watch as one of the creators behind Ameca, the lifelike robot that went viral on social media, shows off more of its lifelike behavior at CES 2022. Then we take a stroll through memory lane back to 2019 when the creator of Sophia discusses his thoughts on the future of robotics and AI.

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** Data Science Certification Training: https://www.edureka.co/data-science **
This Edureka's live session on "Introduction To Machine Learning" will help you understand the basics of Machine Learning and how it can be used to solve real-world problems. The following topics are covered in this session:

01:50 Need For Machine Learning
07:17 What is Machine Learning?
09:32 Machine Learning Definitions
11:58 Machine Learning Process
18:42 Types Of Machine Learning
26:11 Type Of Problems Solved Using Machine Learning
29:32 Demo

Blog Series: http://bit.ly/data-science-blogs
Data Science Training Playlist: http://bit.ly/data-science-playlist

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#edureka #edurekaMachineLearning #machineLearning #machineLearningBasics #machineLearningForBeginners #machineLearningTraining #machineLearningCourse

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About the Course

Edureka's Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling 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. Analyze 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. Analyze 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.

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For online Data Science training, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.