Creating a classifier for terrain dataset and calculating the accuracy using different values of C and gamma
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Updated
Apr 22, 2018 - Python
Creating a classifier for terrain dataset and calculating the accuracy using different values of C and gamma
Codes for various important numeric method computation done during the course ESO208
Creates a fixed graph and determines the shortest path in Python using NetworkX and PyLab.
A random walk model for diffusion of a drop of dye in water.
Python code to render a latex to image, connects to mathPix API to get proper response
Massachusetts Institute of Technology course MITx 6.00.2x "Introduction to Computational Thinking and Data Science" (Winter 2019). An introduction to using computation to understand real-world phenomena. John Guttag, Professor of CS and EE, Massachusetts Institute of Technology. Part 2 of »Computational Thinking using Python« XSeries® program on…
Gráficas hechas en python
Problem set solutions for MITx: 6.00.2x (Introduction to Computational Thinking and Data Science), intermediate MOOC course
A simulation of Roombas cleaning a rectangular room with GUI and statistical analysis.
Creating a classifier for email sent by two persons and calculating the accuracy using SVM. Plotting the dataset.
🎓 A collection of Problem Sets for "MITx: 6.00.2x Introduction to Computational Thinking and Data Science", edX, March-May, 2021.
Physical and Data Link Layer funtionalities of the TCP/IP Model. Manchester Encoding, Cyclic Redundancy Check (CRC), Frame by Frame communication and plotting graphs by PyLab.
Projects and Exercises created on the Course: Introduction to Computational Thinking and Data Science (MITx 6.00.2x) provided by the Massachusetts Institute of Technology (MIT) on EDX platform.
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