Data Mining for Beginners | Data Mining Full course | Learn Data Mining in 10 Hours | Great Learning скачать в хорошем качестве

Data Mining for Beginners | Data Mining Full course | Learn Data Mining in 10 Hours | Great Learning

🔥1000+ Free Courses With Free Certificates: https://www.mygreatlearning.com/acade... Earn a prestigious Data Science certificate from MIT Professional Education. Enroll now and elevate your skills! https://www.mygreatlearning.com/mit-d... Jumpstart your career in Data Science with our course designed for freshers. Apply now to learn more! https://www.mygreatlearning.com/pg-pr... Watch this 10-hour tutorial on Data Mining! Simply put, data mining is used to turn raw data into meaningful information. To keep up with the ever-evolving aspects of data and its domains, data handling and analysis has become crucial to understanding the information that comes attached to it, and that is exactly why data science has come such a long way, in which data mining is considered to be one of the crucial methods to identify patterns and trends in huge datasets. Great Learning brings you this beginner-friendly tutorial on Data Mining to take you from the starting point through the finishing point of everything you need to know about this domain and getting started on the journey to master it. This video starts off with an introduction to Python, followed by understanding a variety of Python libraries. Then we look at the concepts of anomaly or outlier detection. Following this, we will understand Machine Learning in detail and cluster analysis with K-means. Finally, we look at regression analysis in data mining! This video teaches Data Mining and its key functions and concepts with a variety of demonstrations & examples to help you get started on the right foot. 🏁 Topics Covered: 0:00:00 Introduction 0:02:21 Agenda 0:04:46 Basics of Python 0:23:39 Installing Python 0:37:16 Variables and Operators in Python 0:59:54 Data Types in Python 1:29:51 Conditional and Looping Flow Control Statements in Python 1:48:56 Introduction to Python Libraries 1:56:54 Numerical Computation with Numpy 2:11:42 Functions in Python 3:34:33 Data Wrangling with Pandas 4:49:14 Data Visualization with Python: Seaborn & Matplotlib 5:48:53 Anomaly or Outlier Detection 7:04:00 Introduction to Machine Learning 7:26:22 Cluster Analysis with K-means 8:07:51 Regression Analysis in Data Mining 9:16:19 Logistic Regression 🔥Check Our Free Courses with free certificate: 📌Data Science with Python Course: https://glacad.me/344isSU 📌Machine Learning with Python: https://www.mygreatlearning.com/acade... 📌Machine Learning with AWS: https://www.mygreatlearning.com/acade... 📌Machine Learning Algorithms: https://www.mygreatlearning.com/acade... 📌Basics of Machine Learning: https://www.mygreatlearning.com/acade... ⚡ About Great Learning Academy: Visit Great Learning Academy to get access to 1000+ free courses with free certificate on Data Science, Data Analytics, Digital Marketing, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity, Software Development, and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. ⚡ About Great Learning: With more than 5.4 Million+ learners in 170+ countries, Great Learning, a part of the BYJU'S group, is a leading global edtech company for professional and higher education offering industry-relevant programs in the blended, classroom, and purely online modes across technology, data and business domains. These programs are developed in collaboration with the top institutions like Stanford Executive Education, MIT Professional Education, The University of Texas at Austin, NUS, IIT Madras, IIT Bombay & more. SOCIAL MEDIA LINKS: 🔹 For more interesting tutorials, don't forget to subscribe to our channel: https://glacad.me/YTsubscribe 🔹 For more updates on courses and tips follow us on: ✅ Telegram: https://t.me/GreatLearningAcademy ✅ Facebook:   / greatlearningofficial   ✅ LinkedIn:   / verification   ✅ Follow our Blog: https://glacad.me/GL_Blog