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Z30G0D / count_coins
Created April 6, 2018 14:08
Simple exercise with OpenCV to count coins
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Short Opencv Exercise for counting money\n",
"Just a random exercise "
]
},
@Z30G0D
Z30G0D / Week_3_Deeplearning.ai
Last active April 2, 2018 09:10
Week 3 exercise of Andrew NG Deep learning.ai
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Autonomous driving - Car detection\n",
"\n",
"Welcome to your week 3 programming assignment. You will learn about object detection using the very powerful YOLO model. Many of the ideas in this notebook are described in the two YOLO papers: Redmon et al., 2016 (https://arxiv.org/abs/1506.02640) and Redmon and Farhadi, 2016 (https://arxiv.org/abs/1612.08242). \n",
"\n",
@Z30G0D
Z30G0D / Convolutional_NN_Application
Created March 21, 2018 09:31
CNN course #3 in deeplearning.ai CNN_application task
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Convolutional Neural Networks: Application\n",
"\n",
"Welcome to Course 4's second assignment! In this notebook, you will:\n",
"\n",
@Z30G0D
Z30G0D / Convolution_course_PA_1
Created March 19, 2018 14:40
First convolution exercise from Andrew NG course of deeplearning.ai
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Convolutional Neural Networks: Step by Step\n",
"\n",
"Welcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forward propagation and (optionally) backward propagation. \n",
"\n",
@Z30G0D
Z30G0D / OPENCV_1
Last active March 16, 2018 14:33
OpenCV course session 1
This file has been truncated, but you can view the full file.
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"nbpresent": {
"id": "eff3a02c-cf13-4c08-b2b3-df48c676159c"
}
},
"source": [
@Z30G0D
Z30G0D / Exercise4_coursera_Machine_Learning
Created March 13, 2018 09:10
The 4th exercise from machine learning course by Andrew NG including feed forwad
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hey all!\n",
"## Coursera's Machine Learning course- Exercise 4\n",
"<br>\n",
"This is the 4th exercise of the course concerning building of neural networks from scratch.<br>\n",
@Z30G0D
Z30G0D / Logistic_regression_ex2
Created February 17, 2018 13:15
This is the second exercise from Andrew NG course in Machine learning
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exercise 2- Andrew NG Machine Learning Course\n",
"## Hey all!\n",
"This is the second task from Andrew NG course of machine learning concerning simple **logistic** regression.\n",
"I implemented the exercise in python but the original implementation is in MATLAB.\n",
@Z30G0D
Z30G0D / Naive_bayes_classifier
Created February 13, 2018 09:29
A simple naive bayes classifier for spam emails
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Naive Bayes Classifier\n",
"## Spam emails classifier\n",
"\n",
"Hello all, I wanted to build a spam classifier based on the naive bayes classifier.<br>\n",
@Z30G0D
Z30G0D / Elipse_detector
Last active February 7, 2018 10:55
Elipse detector
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Elipse detector through DL neural network\n",
"## Hey, this is my solution for the task.<br>\n",
"First we are going to build are dataset according to the guidelines given.\n",
"<br>\n",
@Z30G0D
Z30G0D / Coursera_Linear Regression
Created January 24, 2018 19:25
Coursera's machine learning course,
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exercise 1- Andrew NG Machine Learning Course\n",
"## Hey all!\n",
"This is the first task from Andrew NG course of machine learning concerning simple linear regression.\n",
"I implemented the exercise in python but the original implementation is in MATLAB.\n",