Anaconda Python KNIME & Orange Installation
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This document provides an overview and installation instructions for machine learning basics using various tools and libraries. It discusses installing and setting up Orange, KNIME, Anaconda, and related Python libraries. Key steps include downloading installers, setting paths, defining workspaces, installing extensions, and creating workflows in Orange and KNIME. Popular cheminformatics and deep learning libraries supported include RDKit, DeepChem, numpy, and scikit-learn.
Anaconda Python KNIME & Orange Installation
- 1. Basics & Installation for ML I am Girinath Pillai @giribio
- 3. Installation Guidelines Letâs start with the ïŹrst set of slides D1-0
- 4. â 4 Video Demo - Installation
- 5. â 5 Github - Installation Instructions
- 6. I 6
- 9. II 9
- 11. KNIME Installation 11 Installation OS Set path Set Memory DeïŹne Workspace
- 12. Install Extensions 12 Extensions Add - link or archives Copy jar ïŹles to âdropinsâ Install from link Experimental Partners Trusted Partners Version speciïŹc
- 13. Create a Workflow 13 KNIME workïŹows are stored within the workspace WorkïŹow group could be created under the workspace WorkïŹow could be imported to the workspace Public KNIME server and KNIME hub has example workïŹows of several extensions
- 14. KNIME Interface 14 Recommended to own a KNIME hub account (free) WorkïŹow editor has notes option External binaries could be integrated Python scripts could be integrated via conda
- 15. Nodes and Usage 15 Node Repository Node description Node Console
- 16. Configure 16 DeïŹne setting Formats Conditions etc Parameterization Memory policy Filters
- 17. III 17
- 18. Anaconda 18
- 19. Installers 19 Miniconda is also an option Anaconda includes Navigator, Jupyter Notebook, Libraries, Orange and others
- 21. Selected Libraries 21 DeepChem Open-source toolchain for deep learning in the drug discovery, quantum chemistry, and other life sciences RDKit General-purpose machine learning and cheminformatics software written in C++ and Python. Some of the functionality includes reading and writing molecules, substructure searching, chemical transformations, or molecular similarity. CACTVS Cactvs is a universal, scriptable cheminformatics toolkit, with a large collection of modules for property computation, chemistry data file I/O and other tasks Cinfony API to several cheminformatics toolkits (Open Babel, RDKit, the CDK, Indigo, JChem, OPSIN and cheminformatics webservices MDAnalysis An object-oriented library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats MDTraj Package for manipulating molecular dynamics trajectories with support for multiple formats nglView A Jupyter widget to interactively view molecular structures and trajectories.
- 22. Selected Libraries 22 numpy A library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays matplotlib A plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits scikit A free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines GromacsWrapper A Python package (Python 2.7.x and Python > 3.4) that wraps system calls to Gromacs tools into thin classes. This allows for fairly seamless integration of the gromacs tools into Python scripts. Seaborn A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics
- 23. IV 23
- 24. V 24
- 25. VI 25
- 26. Thanks! Any questions? You can ïŹnd me at @giribio & pillai@nyroindia.org 26