Doświadczenie zawodowe:
no commercial experience in the field of IT
Edukacja:
Design engineer
Lawyer (law)
Umiejętności zawodowe i inne:
Entry to ML tasks, NumPy, Pandas, Pandas (Data Visualization) . Feature Engineering, Linear Regression, Regularization, ML metrics. Metric models, Straight spaces, class imbalance, Decision trees, SVM. Clustering, Clustering (part 2). Dimensionality reduction, Time series, Text-based robotics, Fundamentals of neural networks, CNN, Seq-To-Seq, Transformers, Diffusion models, OpenCV, Reinforcement learning, Acquaintance. The program is safe, bash, pip, control system versions: view, git, git stream, conflicts. Flask, Flask, REST, Flask, Database, Context Manager, Database Writer, Debugger, Threads, Processors, Threading, multiprocessing, Celery, Docker, Docker Compose, SqlAlchemy, SQL Alchemy, postgres, API Call Plugin, Migrations, Flask Sessions, Django, Django, database, Django Query, URLs, Dodaemo functionality, templates, Django session and core, Testing, Django Tests Fixtures, aiohttp, aiohttp in practice, MongoDB, Adding a bot, aiohttp Session, Cloud (AWS), Cloud (GCP), Cloud (Azure),Basic
concepts of Python, Git. Input/output operations in the console, Operators. IF structure,
loops, strings. Random. Regular expressions, lists, tuples, sets, dictionaries. namedtuple.
Functions, Sorting algorithms, Classes, Exception handling, Working with files, Queries,
Scraping And also additionally studied: Memory.GIL. And a little about software
development methodologies, DRY.KISS.SOLID, Binary number system. Business
operations. Repetition of conditional constructions and ternary operators.
Dodatkowo:
Easy to train, active and perseverance are my main features
