Machine Learning with R
In the Data Science training with R, you will learn data science skills ranging from preparing your data for analysis or modeling to creating and utilizing forecasting, machine learning, deep learning, and artificial intelligence algorithms, and integrating them with databases. During the training, you will apply methodologies that are crucial for decision-making in marketing, finance, business, healthcare, and government institutions to real-world problems encountered in the workplace.
Training table
Machine Learning with R
Machine Learning with R
Maschinelles Lernen mit R
Машинное обучение с R
Information about the training
During the training, you will learn to apply machine learning algorithms developed in recent years, such as Logistic Regression, Decision Trees, XGBoost, CatBoost, LightGBM, FastAI, and Neural Prophet, as well as deep learning methods like RNN and CNN. Additionally, you will learn various techniques for evaluating your models, including Precision, Recall, ROC Curve, and Gini Coefficient. These new skills will enable you to perform descriptive and predictive analysis on data. The course covers a wide range of practical topics from simple to complex, making it suitable for those who wish to analyze large volumes of data and make decisions in enterprises and companies. It will also help participants become competitive in the job market and advance their data careers quickly by utilizing the most modern and complex capabilities of data science immediately after the training.
Who is this training for?
Those who have knowledge in Data Science and wish to deepen their understanding with more modern and complex topics, individuals looking to learn advanced machine learning topics using R programming, programmers and data engineers wanting to learn analytics, Business Managers, Business Analysts, Data Analysts, those interested in and learning Data Analytics, individuals wanting to work with large datasets, researchers, students and professionals seeking to build a career in Data Science, and those preparing or wanting to prepare reports through data analysis in sales, supermarkets, telecommunications, banking, and other business sectors or government institutions.
Certificate
Individuals who successfully complete the training will receive a Certified Machine Learning with R certificate, while other participants will be awarded a participation certificate. You can see a sample certificate on the right.
Machine Learning with R | Machine Learning Algorithms
Machine Learning with R
edureka!
This "Machine Learning with R" video by Edureka will help you to understand the core concepts of Machine Learning followed by a very interesting case study on Pokemon Dataset in R. Video Courtesy: edureka!
Syllabus
Session 1
- What is Machine Learning?
- Linear Modeling
- Measuring the Accuracy of Linear Models
Case Study 1
Predicting a Citizen's Criminality or Risk Level Using a Linear Regression Model.
Session 2
- Logistic Regression
- Weight of Evidence (WOE)– Explanation Power of Predictive Parameters
- Measuring the Accuracy of Logistic Regression Models
- Precision, Recall, ROC, AUC Curve, Gini Coefficient
Case Study 2
Building a Debt Risk Prediction Model Using Logistic Regression with Real Bank Data.
Session 3
- Automated ML, Hyperparameter Tuning
- AutoML - Automated Machine Learning
- Hyperparameter Tuning
- Cross Validation & Imbalance
- Explanation of Black Box Algorithms, Stacked Ensemble Modeling
Case Study 3
- HR Management Case: "Employee Turnover" Data
- Identifying and Deploying the Leading Model Using Different ML Algorithms (Classification Models on Real Employee Turnover Data).
Session 4
- Deep Learning and AI-Based Time Series Analysis
- Data Augmentation for Prophet
- Application of Prophet and Neural Prophet Algorithms
- R Spark
Case Study 4
Forecasting Sales Using Prophet and Neural Prophet Algorithms.
Session 5
- FastAI
- Natural Language Processing (Word Embeddings, "Attention is All You Need")
- Text Classification with Transformers
Case Study 5
Building NLP Models with Real Data in R.
Trainers
Turqut Abdullayev
AZERCONNECT GROUP-DA ANALİTİKA KOMANDASININ RƏHBƏRİTurgut Abdullayev, with over 5 years of experience in the field of data, currently works as the Head of the Analytics Team at Azerconnect Group. Our trainer is the first and only Azerbaijani to receive the international title of "R Contributor." He was the first to develop the "fast.ai" library in the R programming language, and this integration was supported by the founder of the library, Jeremy Howard.
List of Contributors from Official R Website
His previous work experience includes:
* Head of the Limits Management Department at Kapital Bank
* Senior Data Scientist at Access Bank
He has extensive knowledge of software tools such as R, Python, HTML, SQL, Docker, CI/CD (Github Actions), Git, Markdown, and LaTeX, and has worked as a professional data analyst in various consulting companies. In particular, he has mastered the intricacies of machine learning and artificial intelligence through R programming and always incorporates the latest developments in this field into his training sessions. He is also the author of numerous blog posts in the field.