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AI Tools: From GPT4 Turbo to PyTorch

AI Tools: From GPT4 Turbo to PyTorch
  • GPT4 Turbo:
  • tensorflow: https://www.tensorflow.org/

Overciew:

  • AI: GPT4, Machine Learning, Natural Language Processing, Algorithms
  • ML:

Laesst

  • [GPT4] Turbo
  • GPT4: Advanced Data Analysis (Custom Instructions), DALL-E 3, Plugins, Custom Instructions, API

Top AI Tools

  1. TensorFlow and Keras: Open-source libraries for numerical computation and machine learning that enable easy construction and deployment of ML models.
  2. PyTorch: A Python library popular for deep learning applications, known for its flexibility and ease of use in research settings.
  3. Scikit-Learn: A Python library for simple and efficient tools for data mining and data analysis, particularly good for beginners.
  4. Pandas and NumPy: Essential for data manipulation and analysis, these Python libraries offer data structures and operations for manipulating numerical tables and time series.
  5. Jupyter Notebooks: An interactive computing environment that allows for code writing, data visualization, and sharing of analysis.
  6. OpenAI Gym: A toolkit for developing and comparing reinforcement learning algorithms.
  7. Apache Spark: An analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning, and graph processing.
  8. RapidMiner: A data science platform that provides an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.

Tensorflow

  1. Prepare data: Use TensorFlow tools to process and load data.
  2. Build ML models: Use pre-trained models or create custom ones.
  3. Deploy models: Run on-prem, on-device, in the browser, or in the cloud.
  4. Implement MLOps: Run models in production and keep them performing.

AI, Agile & Tech Toolbox 2024

Toolbox 2024 overview:

  1. AI: GPT4 Turbo, Dalle-3, GPTs Agents(Assistants), APIs
  2. Business:
    1. Agile: Scrum, MVP, Kanban, Lean, cross functional team
    2. Scrum: JIRA, Backlog, Sprints, Board, User Stories, AC, Plan, Daily, Reviews & Retros
    3. PM: Social skills, planning, Roadmap, stakeholder management, project delivery, Migration
    4. Finance: Analytical skills, reports, BI, problem solving,
    5. DOCS: Confluence, MKODCS, markdown, GDOCS (docs, sheets, slide), Slack
  3. TECH & Automation:
    1. DEV: VSC, Python, FastAPI, MongoDB, JSON, Jinja2, HTML, JS, CSS
    2. Devops: Linux (WSl, Ubuntu), bash, nano, NGINX, Docker, DC, Cloud (AWS, GCP, Azure), CI/CD, build, test, deploy

Topics

Agile Tools

  • GPT4 Turbo
  • Dalle-3
  • GPTs (Assistants)

Agile Methodologies

  • Scrum: Focuses on sprints, daily stand-ups, sprint planning, reviews, and retrospectives.
  • Kanban: Emphasizes continuous delivery without overburdening the team.
  • Lean Development: Prioritizes customer value and efficient workflow.
  • Pair Programming: Involves two developers working together at one workstation.

Scrum Elements

  • Sprints: Time-boxed iterations for developing a product increment.
  • Daily Stand-Ups: Quick meetings to discuss progress and obstacles.
  • Sprint Planning: Session to plan the work for the upcoming sprint.
  • Sprint Review & Retrospectives: Meetings to assess the sprint and identify improvements.

Product Backlog Development

  • User Stories: Descriptions of software features from an end-user perspective.
  • Acceptance Criteria: Conditions that a software product must satisfy to be accepted by a user.
  • TDD (Test-Driven Development): A software development process that relies on the repetition of a short development cycle.
  • DOR (Definition of Ready): Criteria that determine if a user story is ready to be worked on.
  • DOD (Definition of Done): Criteria that determine if a task in a sprint is completed.

Prioritization and Execution

  • Cross-Functional Team: A group with different functional expertise working toward a common goal.
  • Analytics: Data-driven approach for decision-making.
  • Stakeholder Management: The process of managing the expectation of individuals with an interest in a project.

Tools

  • Mkdocs: A static site generator geared towards project documentation.
  • GitHub/GitLab: Platforms for software development version control using Git.
  • Google Docs: A web-based document management application.
  • JIRA: A tool for issue tracking and project management.
  • Confluence: A collaboration software program.
  • Slack: A messaging app for teams.
  • Python: A high-level programming language.