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6 database teachers in Casablanca

Mustafa

21€

60-min

/h

Data Mining Algorithms Training CourseTranslate this text using Google Translate.

Data Mining Algorithms Training CourseTranslate this text using Google Translate.

Data Mining Algorithms and Techniques Training Course - Beginner and Intermediate Level, for Computer Science Professionals and Non-Professionals. The course content (according to my book published on Google Books), is titled: Advanced Analysis and Data Mining. The book can be searched for using its name or the author's name. Table of Contents Chapter 1: Introduction to Advanced Analysis and Data Mining 1-1 What is data mining, its procedures and tools 1-2 What type of data is mined? 1-3 What are databases? 1-4 Relational Database 1-5 Query Language 1-6 Benefits of Database Mining 1-7 months data mining applications A - Business Intelligence (Business Intelligence) B - Internet search engines Chapter Two: Data Recognition 2-1 Data Types, Characteristics, and Features 2-2 Statistical Description of Data 2-3 Visualization of Data 2-4 Measuring data similarity and difference Chapter Three: Preparing Data for Analysis and Mining 3-1 The importance of preparing data for analysis and mining 3-2 Data Cleanup 3-3 Data Integration 3-4 Data Reduction 3-5 Data Transformation and Data Individualization Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules 4-1 Basic Concepts 4-2 Shopping basket analysis (example) 4-3 Evaluating the dependency and correlation rules being explored 4-4 Mining Multi-Level Dependency and Linkage Rules 4-5 Mining multidimensional dependency and correlation rules 4-6 Rules of nominal and quantitative dependency and correlation 4-7 Exploring and identifying rare and negative patterns 4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage 4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones 4-10 Measuring the type and strength of the relationship in dependency and correlation rules 4-11 Applications of pattern mining in practical life Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms 5-1 Basic Concepts 5-2 Classification using decision tree extrapolation 5-3 Classification using probability theory (hypothetical theory) 5-4 Classification using hypothetical network theory 5-5 Classification using correlation rules extrapolation 5-6 Classification using neural network algorithm 5-7 Classification using the nearest neighbor algorithm 5-8 Multi-category classification algorithms 5-9 Evaluating the efficiency and selection of classification algorithms Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms 6-1 Basic Concepts 6-2 Clustering by Division 6-3 Hierarchical Clustering A. Hierarchical clustering b. Hierarchical fission 6-4 Probability Clustering 6-5 High-Dimensional Clustering 6-6 Clustering of graphs and network data 6-7 Conditional Clustering 6-8 Cluster Segmentation Assessment Chapter Seven: Analyzing and Mining Outliers and Complex Data Types 7-1 Basic Concepts 7-2 Types of extreme values 7-3 Ways to Explore Extreme Values 7-4 Complex Data Analysis and Mining Chapter Eight: Planning Data Mining Operations and Their Applications in Society 8-1 Planning Data Mining Operations 8-2 Data Mining in the Community 8-3 Data mining applications in vital areas of society 8-4 Practical Application: Recommendation System Usage Scenario Appendix 1: Database Fundamentals Appendix 2: Data Warehouse Fundamentals Appendix 3: Glossary of Data Mining Terms

Rachid

verified teacher icon
4.0

3 reviews

(3)

34€

60-min

/h

trusted teacher iconTrusted teacher

Machine Learning and Data Mining Services for your business to know the exact decisionsTranslate this text using Google Translate.

Machine Learning and Data Mining Services for your business to know the exact decisionsTranslate this text using Google Translate.

I am a Data Scientist / Statistical Engineer who specializes in machine learning and data mining services. I have a great experience in the analysis of données and the mise in place of predictive models for the enterprises at the beginning of the decisions. He proposed designing machine learning and data mining services for companies to help on an additional level of public life. Message domains included: Aggression styles: linéaire, logistique, multinomiale, poisson, etc. Classification patterns: arbres de decision, forêts aléatoires, SVM, etc. Clustering: k-means, DBSCAN, etc. Réseaux de neurons: Réseaux de neurones artificiels, Réseaux de neurones convolutifs, Réseaux de neurones récurrents, etc. Traitement du langage naturel: sentiment analysis, text classification, etc. Chronology analyzes of events: ARIMA, SARIMA, etc. I want you to help prepare your données, install models, improve performance and the developer. I use these tools to use Python, R, TensorFlow, Keras, PyTorch, scikit-learn, etc. Don't hesitate to contact me if you have something to do for your machine learning and data extraction projects. I am available for individual descriptions, formations or major projects.

Mousab

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5.0

1 reviews

(1)

19€

60-min

/h

trusted teacher iconTrusted teacher

Mr: Mousab -Training and courses: Merise and databaseTranslate this text using Google Translate.

Mr: Mousab -Training and courses: Merise and databaseTranslate this text using Google Translate.

The Merise course is a methodology for the design and development of information systems, in particular databases. It is structured around different steps to analyze, design and implement a database in an IT environment. Here is a general description of the main elements of the Merise Database Management course: When using the Merise methodology for database design, one generally works with three main types of models: MCD - Conceptual Data Model: The Conceptual Data Model is a representation of entities, their attributes and the relationships between them, independent of any technical aspect. It is often developed using Entity-Relationship (ER) diagrams. MCD focuses on representing business concepts and the relationships between them. It allows you to visualize the major entities of the organization and their interactions. MMD - Multidimensional Model: The Multidimensional Model is particularly used in the field of data warehousing. Unlike the traditional relational model (used in operational databases), the multidimensional model is designed to analyze data along different dimensions. It is based on data cubes containing measurements and axes (dimensions) to analyze these measurements. This model is more suitable for decision analysis. MPD - Physical Data Model: The Physical Data Model is a concrete and technical representation of the structure of the database. It takes into account the specificities of the database management system (DBMS) chosen for implementation. MPD focuses on implementation details such as tables, columns, data types, indexes, constraints, etc. These three models are generally used as part of the Merise methodology to gradually move from an abstract and conceptual representation of data (MCD) to a more concrete and technical representation (MPD) while taking into account the specific needs of the organization or the project. MMD, on the other hand, is more oriented towards data analysis for decision-making processes and is not directly linked to the physical structure of the database.

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Our students from Casablanca evaluate their Database teacher.

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Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.9 out of 5 based on 32 reviews.

I was able to get 20 out of 20 from my Excel exam in university, thanks to our classes with Mr Salah. I had 0 knowledge on excel before but after learning and exercising with Mr Salah, I got the maximum grade on my exam. Finally now, I really feel confident about my Excel knowledge, all thanks to Mr Salah. I would really recommend it to anyone who has problems with Excel.

To ensure the quality of our Database teachers, we ask our students from Casablanca to review them.

Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.9 out of 5 based on 32 reviews.

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