“Learn about Data Mining Standard Processes, Survival Analysis, Clustering Analysis, Various algorithms and much more.”
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课程内容
Introduction to Data Mining Data Mining Standard Processes Survival Analysis Cox Hazard Regression Introduction to Clustering Analysis Dimensionality Reduction Association Rule Learning Tree Based Models Introduction to Boosting Models Model Explanationability Outro Section Bonus Section
Develop SSAS cubes from data warehouse on Multidimensional & Tabular modes with Dimensional & Data Mining Models
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课程内容
Introduction Fundamentals and Technology Overview SQL Server Analysis Services (SSAS) Installation Cube Design and Development Multidimensional Expressions – Practical code development Administration Advance Techniques Performance Tuning Basics of Data Mining Concepts and Data Mining Algorithms Developing Data Mining Models using SQL Server and SSAS Tabular SSAS – Installation and Setup SSAS Tabular Data Model – Design and Development Conclusion
Learn how to prepare your data for great analytics in R.
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课程内容
Introduction Data Import and Data Structuring Cleaning Your Data Querying and Filtering Data with data.table Queries and Filtering Exercises Using dplyr on one and multiple Datasets Integrate SQL into R Detecting Outliers Working with Strings – Regular Expressions Working with Dates and Time
“Learn Regression Techniques, Data Mining, Forecasting, Text Mining using R”
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课程内容
Introduction To Data Science Basic Statistics Hypothesis Testing Introduction Hypothesis Testing- Parametric Hypothesis Testing-Non Parametric BASICS OF R-PROGRAMMING Predictive Analytics Data Mining/Clustering Using R Clustering on Mixed Data High Dimension Data Analysis – Dimension Reduction Relationship Mining – Association Rules Recommendation System Text Mining Using R Forecasting Using XL Miner Bonus: Forecasting Model Based Approaches Bonus: Forecasting Data Driven Approaches Interview Q&A’s
“Learn to use R software for data analysis, visualization, and to perform dozens of popular data mining techniques.”
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课程内容
“Data Types and Structures in R Data and File Input and Output Visualizing (Getting to Know) your Data Decision Trees and Random Forests Linear Modeling (Regression) and Generalized Linear Modeling (GLMs) K-Means, K-Medoids, and Hierarchical Cluster Analysis Approaches Density-Based and Agglomerative Hierarchical Clustering More Cluster Analysis Examples, Graphics, and Detecting Outliers K-Means TAM Residuals Cluster Analysis Software Case example”
“Harness the Power of Machine Learning in R for Data/Text Mining, & Natural Language Processing with Practical Examples”
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课程内容
INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools Reading in Data from Different Sources in R Exploratory Data Analysis and Data Visualization in R Data Mining for Patterns and Relationships Machine Learning for Data Science Unsupervised Classification- R Dimension Reduction Supervised Learning Theory Supervised Learning: Classification Supervised Learning: Regression Introduction to Artificial Neural Networks (ANN) More Web-scraping and Text Data Mining Gaining Insights from Text Data- Text Mining and Natural Language Processing (NL Text Data and Machine Learning Miscellaneous Lectures
“How to perform market basket analysis, analyze social networks, mine Twitter data, text, and time series data.”
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课程内容
“Introduction to R and to Data Mining Association Analysis (part 1) Association Analysis: Online Radio and Predicting Income Social Network Analysis: iGraph Visualizations Social Network Analysis (part 2) Text Mining Twitter Data Text (String) Manipulation Time Series Data Mining Case Study: Forecasting House Price Indices in Canberra, Australia”
“Learn Data Analysis and Mining, Machine Learning, Deep Learning in Python & PySpark”
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课程内容
Introduction to Data Mining & Machine Learning in Python (Course 1) Setup Programming Environment Supervised Learning Algorithms Unsupervised Learning Algorithms Deep Learning Introduction to Learn Data Analysis in PySpark (Course 2) Introduction to PySpark Development Environment Cleaning and Transformation Data in PySpark Performing Data Analysis in PySpark Appendix: Statistics Overview
Learn All the Skills to Become a Data Mining & Machine Learning Scientist [2022] [COMPREHENSIVE MASTERCLASS]
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课程内容
“Introduction ********** Setting up the Environment ************ Setting up the Environment for Python Machine Learning ********** Python Basics For Machine Learning *********** Python For Absolute Beginners – Lectures Software Design for Beginners ********** Understanding Data With Statistics ******** Statistics For Data Scientists & Machine Learning Engineers ********** Data Pre-processing ************ Data Visualization with Python ********** Machine Learning ************** Artificial Neural Networks [ Comprehensive Sessions]Naive Bayes Classifier with Python [Lecture & Demo]Natural Language Processing for Data Scientists Linear regression Logistic regression Decision Trees Introduction to clustering [K – Means Clustering ]********** Deep Learning Masterclass 2022 **************** Deep Learning Masterclass 2022 (Video Sessions and from Top Universities) New York University : NYU Deep Learning SP21 Deep Convolutional Generative Adversarial Networks (DCGAN) & GAN 1 Extra Reading ********** Java & Web For Data Scientists ******** Java programming for Data Scientists Java – Concurrent Programming Web Development for Data Scientists ********** Machine Learning / Deep Learning Projects with Source code ***** Self-supervised learning in Computer Vision with Yann LeCun, Alfredo Canziani, AutoNovel: Automatically Discovering and Learning Novel Visual Categories [code]Facebook AI Releases ‘BlenderBot 2.0’: An Open Source Chatbot [Code & Paper]Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval [Code & Paper]Image Search multilingual text2image search for 50+ languages. Presentation video for “Depth from Camera Motion and Object Detection,”CVPR 2021 Real-Time Super-Resolution System of 4K-Video Based on Deep Learning[Code,Paper]DeepFace 0.0.60 Deepface is a lightweight face recognition and facial attribute TensorFlow 2 quickstart for beginners TensorFlow 2 quickstart for experts Basic classification: Classify images of clothing [Code & Guidance]Basic text classification – Code [ TensorFlow ]Introduction to Autoencoders Audio recognition: Recognizing keywords 40 Machine Learning Algorithms with source code and guided tutorial 500+ Artificial Intelligence Projects with source ********** Live Class Recordings 2022 ********* Live Class Recordings – Introduction to Program Design Live Class Recordings – Concurrent Programming Live Class Recordings – Machine Learning & Data Mining -L5 [2022]Research Discussions Live Class Recordings – Machine Learning & Data Mining -L7 [2022]Advanced Big Data Analytics”
有数以千计的在线课程和课程可以帮助您提高 数据挖掘 技能并获得 数据挖掘 证书。