Lesson 5: Data Analytics, Data Science and Machine Learning
Data Science
involves gathering,storing,analyzing,and plotting data to effectively extract useful information. Aim: Gain meaningful insights from both structured and unstructured data
Deep Learning Architectures
. Deep Belief Network(DBN) .Convolutional Neural Network (CNN) .Recurrent Neural Network (RNN) .
The influencing factors include:
. Query volume: unique and verifiable users .Geographical locations .Keyword or phrase matches on the web .Scrubbing for inappropriate content
Cloud Storage Platform
.Amazon AWS .Microsoft Azure .Lambda
Analytical Platforms of Machine Learning Algorithms
.Forecasting .Regression .Bayesian network .Vector autoregression
Crime prevention agencies use data science in deciding:
.Where to deploy police manpower? .Who to search at a border crossing? .Which intelligence to consider in counter- terrorism activities?
Data Science Process Flow divide into 3 Steps
1.Data acquisition 2.Data wrangling 3.Analysis,problem solving and business decision.
Data Science and Business St
the process flow of data -driven decision-making process: 1. Define business goals 2.Build a team of data scientists 3.Identify data sources and enable new sources of data capture 4. Design business dashboards to track goals.
RFM analysis
used data science to segment customers into RFM groups and target marketing and promotions.
Travel Companies
uses dataset from social media, itineraries, predictive analytics, and location tracking to arrive at the 360-degree view. The sensors from different modes of transport provide real-time data on various parameters to predict and prevent problems.
Step 3: Machine Learning
validate the model, perform necessary statistical analysis apply machine learning or recursive analysis,run regression testing and compare results against other techniques or sources.
RFM analysis
A technique readily implemented with basic reporting operations to analyze and rank customers according to their purchasing patterns.
Analytical Platforms are
Algorithms Architectures Data Storage Platforms Tools
E-Commerce
Amazon is an e-commerce giant that leverages data science to the fullest extent. Amazon prefers an everything under one roof model.
Crime Agencies
Analytics to track time and identify patterns to derive prediction techniques and prevent future burglaries by analyzing previous data
Types of Data Science
Data Analytics Data Mining Machine Learning
Data Science Domain
Data Mining,Data Analytics,Machine Learning
Step 1: Data acquisitions
Data Scientists work with existing data sets or gather them from various sources and the most important part of the whole process is to have the correct data.
Data Science is
Data cleansing,Trend forecast,Preparation analysis, Machine learning and data analytics.
Data Scientists: Assets to the Business
Empowers Management to make better decisions,Provides insight on various KPI's and parameters,Enables strategic changes for better results,Identifies and refines the target audience and Identifies areas of improvement and Identifies opportunities
Few successful companies that uses data science are
Goggle,Facebook,Alibaba Group
Tools (Analytics Tools)
Spark Python R Apache
Reporting Tools
Tableau Splunk Power BI Kibana
Travel Industry
The business segment that provides transportation, lodging, dining, attractions, entertainment, guide services, and other travel elements related to tourism.
Data Analytics
is the process of examining raw data to draw conclusions about that information Derive Information Derive insights from raw data sources
Data Scientists
an individual who searches through multiple, disparate data sources in order to discover hidden insights that will provide a competitive advantage
Alibaba's Loan
analyzing trading records and evaluates risk and uses predictive models to analyze transaction records and collects data from e-commerce platforms and to determine merçhants creditworthiness
Data Science and Business Strategy
are business owners used to measure their success based only on Profit and Loss Statements. Current era of technology leverages data science for efficient prediction on what will work.
Step 2: Data Wrangling
choose the right tools from Python,R,and SQL ,Derive a clean data set and apply pick -and-shovel algorithms and obtain meaningful data.
Data Scientists
combines both domain and technology perspectives and knows multiple analytical functions and works with data from video and social media sources and has knowledge of technologies such as Python,SAS,R, Scala,visualization libraries, SQL,database,and machine learning.
Machine Learning
creates systems that can learn from the data. It is the ability of machines to predict outcomes based on patterns in the past.
Data Analyst
extracts meaningful insights from various data source and analyzes organizational data
Data Scientists
forecast the future based on past patterns.
Data Scientists
found that the people who pay bill promptly are less prone to the accidents.
Data Mining can help
identify pattern in everything, from domestic violence to terrorism.
Data Mining
is the process of analyzing data to extract information not offered by the raw data alone it helps increase revenue and cut costs.
Data Analytics
is the process of examining raw data to draw conclusions about that information
Machine Learning
learning from past patterns using a set of algorithms and predicts outcomes accurately.
Machine Learning
leverages various algorithms to train the machine.
Facebook uses
machine learning in every -aspect including : Scrolling the news feed and Browsing images or videos
Aliloan is an automated
online system that provides flexible microlans to entrepreneurial online vendors
Advanced analytics can help
prevent crime using information from social media
RFM analysis
recency, frequency, monetary
Google uses data science to provide
relevant search recommendations
The most challenging part of being a data scientists is
taking the results and presenting them to the stakeholders in an easy and consumable manner.