Michał Żarnecki Portfolio

I'm a programmer and lecturer. My work is related to programming in Python/PHP/JavaScript and designing systems and solutions related to AI/machine learning, data mining, big data and natural language processing.

Category: lectures

Generative AI in text Mining – laboratories at the Collegium da Vinci

Posted on 12 July 2024  in lectures

The course familiarizes participants with aspects of generative artificial intelligence and the latest achievements in the field of natural language processing. Participants learn the theoretical foundations and architecture of Large Language Models (LLM) and gain practical skills in working with text data. The course places particular emphasis on understanding popular tasks using LLM such as text generation, machine translation, sentiment analysis, creating summaries and answering questions based on a database of source documents. After completing the course, the participant knows the techniques used in command engineering, metrics for evaluating the results generated by LLM, and methods for improving returned content. He can also apply large text models to a variety of applications in research, industry and other areas.

topics:
Generative AI tasks: translation, question-answer, summarize, sentiment
Architecture and types of LLM, encoder, decoder.
Text vectorization, positional coding, attention mechanism (Multi-Head Attention)
OpenAI GPT, Google Gemini, Mistral Mixtral, Meta Llama, Claude, FLAN models.
Prompt engineering, multi-task instruction fine-tuning, zero/one/few shot learning
Parameter-Efficient Fine-Tuning (PEFT), LoRA
Division of instructions into steps: chain-of-thought
Evaluation of LLM models: performance evaluation, ROUGE/BLEU metrics, benchmark
RAG – Retrieval Augmented Generation, vector database
LLM training computational challenges, scaling laws
Frameworks for working with LLM, LangChain, ReAct

, , , ,

[Top]

Category: lectures

E-learning course: Machine learning – how to use the potential of data to get better results and make smart decisions

Posted on 3 January 2024  in lectures

Course scenario:

  1. Definition and applications of machine learning
    • Data deluge and the definition of machine learning
    • Machine learning examples and related fields of knowledge
    • Types of machine learning
  2. Machine learning tools used in the course
    • Programs used in the course
    • Orange Data Mining
    • Jupyter Lab
  3. Supervised machine learning
    • Machine learning process
    • Data collection, labeling and analysis
    • Feature engineering and division into training and testing sets
    • Model training and evaluation
    • Model export, corrective actions
    • Regression example
    • Classification example
(more…)

, , , , , , , , , , , , , , ,

[Top]

Category: lectures

API in data mining – laboratories at the Collegium da Vinci

Posted on 1 October 2021  in lectures

The “API in data mining” course aims to familiarize students with the tools, libraries and cloud solutions used in data mining. During the course, students will acquire the necessary skills to design complete applications that use cloud-based services to process and collect data. They will gain the ability to integrate and communicate between libraries and data mining tools. The contents of the module introduce you to the basic terms and concepts related to modern data processing pipeline architecture. After completing the course, participants will gain the basic skills necessary to use advanced tools and techniques in working with data and to design and implement cloud-based applications for data processing and collection.


topics:
Definition of API and data mining concepts, application of API in data mining
Cloud computing challenges,ETL and ELT
Specificity of the organization and roles related to working with data.
The structure of applications using machine learning models and big data-related services.
Integration with big data and machine learning services within AWS / Google Cloud AI.
Designing a data processing pipeline using websites to process and collect data.
Data import and preparation, data storage and structuring
Creating a data Lake, creating a data warehouse
Big Data processing
Scaling, containerization and microservices architecture in modern dev and prod env

, ,

[Top]

Category: lectures

Machine learning in Python- laboratories at the Collegium da Vinci

Posted on 1 February 2021  in lectures

The amount of data collected in online resources is growing at an exponential rate. To use the knowledge contained in this data, it is necessary to know machine learning techniques, which are part of the field of artificial intelligence. The module presents pattern mining techniques for both structured data, which follows a clearly defined schema, and unstructured data, which exists in the form of natural language text, signals, or graphics. Courses within the module include pattern detection, training machine learning models, clustering and grouping, text mining, computer vision processing and data analysis, and visualization. Practical exercises during laboratories include, among others: training a model for predicting apartment prices, training a prototype, an autonomous vehicle, using transfer learning to extract information from text, implementing sound and image recognition to control a drone.

topics:
• Python machine learning libraries • Supervised machine learning • Unsupervised machine learning • Reinforcement learning • Natural language processing • Detecting patterns in text data • Text tagging and classification • Topic modeling, semantic analysis • Artificial neural networks • Non-text data analysis: audio • Computer vision processing • Cloud frameworks and solutions in data science

, ,

[Top]