Robotics reviewer

internet of things (IoT)

is the network of physical objects- devices, vehicles, buildings, and other items embedded with electronics, software, sensors, and network connectivity - that enables these objects to collect and exchange data.

Kevin Ashton

he coined the term ‘internet of things’ in 1999

Internet of Things (IoT)

it is a device that collect and transmit data via the internet

2.5 Billion Gigabytes

how many data is generated per day?

Data

it can be any unprocessed fact, value, text, sound, or picture that is not being interpreted and analyzed

Data

the raw facts and figures

Structure

how the data is presented

context

an environment where our prior knowledge and understanding can make sense of data

meaning

data in the correct structure and placed within context

knowledge

the application of information to a solution

text, graphics, sound, moving images

4 types of data representation

information

data that has been interpreted and manipulated and now has some meaningful inference for the users

knowledge

combination of inferred information, experiences, learning, and insights. results in awareness or concept building for an individual or organization

numeric data

if a feature rerpresents a characteristic measured in numbers it is called a numeric feature

categorical data

a categorical feature is an attribute that can take on one of the limited, and usually fixed number of possible values on the basis of some qualitative property

nominal feature

a categorical feature is also called as?

ordinal data

this denotes a nominal variable with categories falling in an ordered list. examples include clothing sizes such as small, medium, and large or a measurement of customer satisfaction on a scale from “not at all happy” to “very happy”

volume

scale of data. with the growing world population and technology at exposure, huge amounts of data are being generated each and every millisecond.

variety

different forms of data - healthcare, images, videos, audio clippings

velocity

rate of data streaming and generation

value

meaningfulness of data in terms of information that researchers can infer from it

veracity

certainty and correctness in data we are working on

structured data

is quantitative data in form of numbers and values

unstructured data

qualitative data in form of text files, audio files, video files.

data science

it is an interdisciplinary field of scientific methods, processes, algorithms, and systems to extract knowledge or insights from data in various forms either structured or unstructure

artificial intelligence

a branch of computer science dealing with the simulation of intelligent behavior in computers

artificial intelligence

a program that can sense, reason, act, and adapt

artificial intelligence

is the programmed reasoning and thinking skills applied to machines to mimic human or animal intelligence.

artificial intelligence

The science and engineering of making intelligent machines, especially intelligent computer programs

artificial intelligence

is an approach to make a computer a robot or a product think how smart humans think

Blaise Pascal

first mechanical, calculating machine built by French mathematician and inventor?

Charles Babbage and Ada Lovelace

first design for your programmable machine is done by?

Warren McCullach and Walter Pitts

Foundations of neural networks established by __________ drawing parallels between the brain and computing machines

Alan Turing

he introduced a test, which is the Turing test, as a way of testing a machine intelligence

ELIZA

_____ is a natural language program that is created. it can handle dialogue on any topic similar in concept of today’s chatbots

Edward Feigenbaum

he creates expert systems which emulate the decisions of human experts

Deep Blue

beats the world chess Garry Kasparov

Roomba

it is an autonomous vacuum cleaner that avoids obstacles

2009

in this year, Google builds the first self driving car to handle urban conditions

AlphaGo

Beats the professional goal player Lee Sedol 4-1

1955

The year where the term artificial intelligence is used for the first time

Arthur Samuel (1959)

he described machine learning as the field of study that gives computers ability to learn without being explicitly programmed

Machine Learning

is the study of programs that are not explicit program but learn patterns as they are exposed to more data over time

Machine Learning

using data to answer questions

Deep Learning

Machine learning that involves using very complicated models called deep neural networks

Deep learning

models that determine the best representation of original data; in classic machine learning humans must do this

Target

predicted category or value of the data

Features

properties of the data use for prediction,(non-target columns)

Label

The target value for a single data point

Supervised learning

use labeled training data to infer model

Regression

predicts continuous valued output

Classification

predicts a discreet valued output

training

Feed training data to learning algorithm

Testing

test the model, using testing set and obtain the predictions based on the trained model

Accuracy

calculated as the number of all correct predictions divided by the total number of the dataset

Recall or Sensitivity

measures the percentage of the actual positive class that is correctly predicted

Precision

Measures the percentage of the predicted positive class that is correct

Specificity

is concerned with how correctly the actual negative class is predicted

F1 Score

is the harmonic mean. it is a nice metric because it uses precision and recall.

Receiver Operating Characteristic Curve

what is the meaning of ROC curve

Mean Squared Error (MSE)

is the mean absolute error. It is the average of the squid aid that is used as the loss function for least squares regression.

Mean Absolute Error (MAE)

it evaluates the absolute distance of the observations (the data set entries) to the predictions on a regression, taking the average of the overall observations

Mean Absolute Percentage Error (MAPE)

is the mean of all absolute percentage errors between the predicted and actual values.

Root Mean Square Error (RMSE)

is the standard deviation of the errors which occur when a prediction is made on a dataset.

formula for accuracy

formula for recall

formula for precision

formula for specificity

formula for f1 score

formula for Mean Squared Error

formula for Mean Absolute Error

formula for Mean Absolute Percentage Error

formula for Root Mean Square Error

Anaconda

is a distribution of the Python and R programming languages for scientific computing that aims to simplify package management and deployment

Python

It’s a popular programming language that was created by Guido Van Rossum and released 1991. It is an interpreted, high-level general, purpose, programming language. It’s language constructs, as well as its object oriented approach aim to help programmers write clear, logical code for small and large scale projects.

Scientific Python Development Environment

meaning of Spyder

SPYDER

A powerful Python IDE with advanced editing, interactive, testing, debugging, and introspection features

JupyterLab

is a next generation web based user interface for project Jupyter

Jupyter Notebook

it is a web based interactive computing notebook environment. Edit and run human readable documents while describing the data analysis.

Colab

I love you to write an execute python in your browser with zero configuration required, access to GPUs fee of charge and EC sharing

Keras

is an advanced programming interface (API) that works for the Tensorflow library.

Matplotlib

is a library that helps with the visualization and plotting

NumPy

Is one of the first libraries that worked with data science. You can use it for mathematical and statistical functions using large n-arrays or multi dimensional matrices.

Numerical Python

what is the meaning of NumPy

Pandas

is another library in Python for data science derived from NumPy

Python Data Analysis

what is the meaning of Pandas

Pytorch

it is a deep learning framework from Facebook’s AI research group.

Tensorflow

it also helps with building neural network

Pandas

it is an open source Python library, providing high performance, data manipulation, and analysis tool, using its powerful data structures

NumPy

it is a Python used for working with arrays. it also has functions for working in domain of linear algebra, fourier transform, and matrices.

Matplotlib

it is a comprehensive library for creating static, animated and interactive visualization in Python.

Seaborn

it is a python data decision library based on matplotlib. it provides a high-level interface for drawing attractive and informative statistical graphics.

Area

it displays graphically quantitative data.

bar plots

it it represents categorical data with rectangular bars with height or lengths proportional to the values that they represent

histogram

it is a plot that helps you discover and show the underlying frequency distribution of a set of continuous data.

line plot

it shows the frequency of data along the number line. It is best to use when a data is time series.

scatter plots

used when you want to show the relationship between two variables

box plots

it is a plot which a rectangle is drawn to represent the second and third quartile, usually with a vertical line to indicate the median value.

hexagonal bin plot

it is another way to manage the problem of having too many points that start to overlap.

kernel density estimation plot

it is a technique that lets you create a smooth curve give a set of data