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Generative AI
3,021 Views · 3 years ago

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In this video on Machine Learning with Python full course, you will understand the basics of machine learning and Python. In this Machine Learning tutorial for beginners, we will cover essential machine learning topics like applications of machine learning and machine learning concepts and understand why mathematics, statistics, and linear algebra are crucial. We'll also learn about regularization, dimensionality reduction, and PCA. We will perform a prediction analysis on the recently held US Elections. Finally, you will study the Machine Learning roadmap. Below are the topics covered in this video:

00:00:00 Machine Learning With Python Full Course 2023
00:08:36 Introduction to Machine Learning
00:16:14 Top 10 Applications of Machine Learning
00:32:38 Types of Machine Learning
00:37:46 Machine Learning Algorithms
00:38:14 Linear Regression
00:46:52 Decision Tree
01:23:25 Clustering
01:26:11 K-Means Clustering
02:18:03 Data and its types
03:29:22 Probability
04:07:53 Multiple Linear Regression
04:45:55 Confusion Matrices
05:59:54 KNN
06:23:40 Support Vector Machine
07:14:40 Principle Component Analysis(PCA)
07:53:01 Corona Virus Analysis

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Dataset Link -https://drive.google.com/drive..../folders/15lSrc4176J

✅ AI ML Course Overview

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

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- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
-GANs
- Keras
- Tensorflow
- Reinforcement Learning
- Speech Recognition
- Recommendation Systems
- Ensemble Learning
- NumPy

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Generative AI
3,073 Views · 3 years ago

🔥Post Graduate Program In Full Stack Web Development: https://www.simplilearn.com/pgp-full-stack-web-development-certification-training-course?utm_campaign=WhatIsDataStructures-CCxgUXrbFWY&utm_medium=DescriptionFF&utm_source=youtube
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This tutorial will provide you an introduction to data structures. This Simplilearn tutorial will teach novices what data structure is and how to use it. We will discover real-world examples of data structures, as well as the types of data structures and their uses, in this data structures tutorial.

The following are some of the themes covered in this video:
00:00:00 Introduction What Is Data Structure?
00:01:21 What Is Data Structure?
00:02:07 What Is Data Structure? and Why do we need Data Structures?
00:04:17 What Is Data Structure? and it's Types
00:06:52 Importance of Data Structures

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#WhatIsDataStructure #IntroductionToDataStructure #DataStructuresTutotorial #DataStrcutureExplained #DataStrcuturesWithExamples #DataStrcutures #DataStructureTutorial #DataStructureAndAlgorithmsTutorial #DataStrcutures #Simplilearn

Introduction to Data Structures?
A data structure is a collection of data pieces that provides an efficient method for storing and organizing data in a computer so that it may be used effectively. Arrays, Linked Lists, Stacks, Queues, and other Data Structures are examples. Data Structures are employed in practically every element of computer science, including operating systems, compiler design, artificial intelligence, graphics, and many more applications.

What Is a Data Structure?
The short answer is: a data structure is a specific means of organizing data in a system to access and use. The long answer is a data structure is a blend of data organization, management, retrieval, and storage, brought together into one format that allows efficient access and modification. It’s collecting data values, the relationships they share, and the applicable functions or operations.

Why Is Data Structure Important?
The digital world processes an increasing amount of data every year. According to Forbes, there are 2.5 quintillion bytes of data generated daily. The world created over 90 percent of the existing data in 2018 in the previous two years! The Internet of Things (IoT) is responsible for a significant part of this data explosion. Data structures are necessary to manage the massive amounts of generated data and a critical factor in boosting algorithm efficiency. Finally, since nearly all software applications use data structures and algorithms, your education path needs to include learning data structure and algorithms if you want a career as a data scientist or programmer. Interviewers want qualified candidates who understand how to use data structures and algorithms, so the more you know about the concepts, the more comfortably and confidently you will answer data structure interview questions.

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Machine Learning
2,207,625 Views · 4 years ago

Generative AI
3,723 Views · 3 years ago

🔥 Professional Certificate Program In Data Analytics: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=DataAnalytics-4GM1I2Us6vA&utm_medium=Descriptionff&utm_source=youtube

Boost your career with this PG in Data Analytics, in partnership with Purdue University & in collaboration with IBM, featuring masterclasses from Purdue University and IBM. The Data Analytics certification program follows a bootcamp model designed with real-life projects and business case studies. This Data Analytics certification course is ideal for all working professionals and prior programming knowledge is not required. It covers job-critical topics like data analytics, data visualization, regression techniques, and supervised learning in-depth via our Bootcamp learning model with live sessions by leading practitioners & industry projects.

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✅8X higher live interaction with 140+ hours of live online classes by industry experts
✅Capstone from 3 domains and 14+ Projects with Industry datasets from Google PlayStore, Lyft, ✅World Bank etc.
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✅Get noticed by the top hiring companies

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