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1.

tutorial

Indian Digits Dataset via CMATERdb in easy to use NumPy format

CMATERdb is the pattern recognition database repository created at the 'Center for Microprocessor Applications for Training Education and Research' (CMATER) research laboratory, Jadavpur University, Kolkata 700032, INDIA. This database is free for all non-commercial uses. More information on CMATER is here.

Dataset Description:

CMATERdb 3.1.1: Handwritten Bangla numeral database is a balanced dataset of total 6000 Bangla numerals (32x32 RGB coloured, 6000 images), each having 600 images per class (per digit).
CMATERdb 3.2.1: Handwritten Devanagari numeral database is a balanced dataset of total 3000 Devanagari numerals (32x32 RGB coloured, 3000 images), each having 300 images per class (per digit).
CMATERdb 3.4.1: Handwritten Telugu numeral database is a balanced dataset of total 3000 Telugu numerals (32x32 RGB coloured, 3000 images), each having 300 images ...

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prabhuomkar/CMATERdb: Easy to use CMATERdb datasets converted in NumPy format

https://github.com/prabhuomkar/CMATERdb

Category: Machine Learning

2.

tutorial

Pro Content

Histograms

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Category: Machine Learning

3.

tutorial

Support Vector Machine (SVM) Theory

In this tutorial, we'll describe the mathematics behind Support Vector Machines. This tutorial is going to be much more math heavy as compared to other tutorials. If you're mostly interested in applying SVMs to solve problems, then our first tutorial on SVMs is sufficient. However, if you would like to understand the mathematical basis of Support Vector Machines, then you'll find this tutorial interesting.

In this tutorial, we will focus on the hard-margin SVM and soft-margin SVM. However, we will not be considering kernels or the hyper-parameter \gamma (gamma).

Problem Formulation

In SVM, the decision function for predicting data points x corresponds to the equation of an hyperplane:

f_w(x) = w^T x + w_0

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Category: Machine Learning

NaN.

course

Learn Python for Data Science and Machine Learning

Overview

This 6-part course teaches python for data science and machine learning.

In this course, you will learn about the following important Python libraries used in Data Science and Machine Learning. Numpy (numerical python) provides vector and matrix primitives in Pytho...

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Syllabus

Introduction to NumPy
Free
16 mins
Hands-on Assignment: Data Exploration with NumPy
Free
63 mins
Introduction to Pandas (follow along)
Free
25 mins
Hands-on Assignment: Data Exploration and Preparation with Pandas
Free
58 mins
Introduction to Data Visualization with Matplotlib
Free
20 mins

Start this course

Introduction to NumPy

Category: Machine Learning

Top comment in this discussion

Joshua Mckay17w

how do i get started

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5.

discussion

Pro Content

Solution to Hands-on Project: Digit classification with K-Nearest Neighbors and Data Augmentation

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Category: Machine Learning

NaN.

tutorial

Pro Content

Dimensionality Reduction and Principal Component Analysis

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Category: Machine Learning

Top comment in this discussion

Frantisek Mraz11w

This is for Pro Members

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