Machine learning is growing very rapidly day by day. We are using machine learning in our daily life even without knowing it such as Google Maps, Google assistant, Alexa, etc.
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
Data Science is the Sexiest job in 21st century. Big Data Concept is going to rule the 21st century. Here is the presentation to give complete information and overview of data science big data.
Machine learning is growing very rapidly day by day. We are using machine learning in our daily life even without knowing it such as Google Maps, Google assistant, Alexa, etc.
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
Data Science is the Sexiest job in 21st century. Big Data Concept is going to rule the 21st century. Here is the presentation to give complete information and overview of data science big data.
SEAMLESS AUTOMATION AND INTEGRATION OF MACHINE LEARNING CAPABILITIES FOR BIG ...ijdpsjournal
The paper aims at proposing a solution for designing and developing a seamless automation and integration of machine learning capabilities for Big Data with the following requirements: 1) the ability to seamlessly handle and scale very large amount of unstructured and structured data from diversified and heterogeneous sources; 2) the ability to systematically determine the steps and procedures needed for
analyzing Big Data datasets based on data characteristics, domain expert inputs, and data pre-processing component; 3) the ability to automatically select the most appropriate libraries and tools to compute and accelerate the machine learning computations; and 4) the ability to perform Big Data analytics with high learning performance, but with minimal human intervention and supervision. The whole focus is to provide
a seamless automated and integrated solution which can be effectively used to analyze Big Data with highfrequency
and high-dimensional features from different types of data characteristics and different application problem domains, with high accuracy, robustness, and scalability. This paper highlights the research methodologies and research activities that we propose to be conducted by the Big Data researchers and practitioners in order to develop and support seamless automation and integration of machine learning capabilities for Big Data analytics.
Data Science is a form of science that focuses on dealing with huge chunks of data by using modern data analysis tools and techniques to discover hidden patterns, meaningful insights, and make critical business decisions.
A Data Science professional has to utilize complicated machine learning algorithms to develop predictive models. There could be multiple sources present in different formats used in data analysis.
Data Mining | How Organizations use Data Mining Techniques | Steps of Data Mining | Advantages and Disadvantages of Data Mining | Recommendation and Conclusion
Email : fahimbd329@gmail.com
LinkedIn : https://www.linkedin.com/in/md-wasiful-alam-fahim-709a84167/
Hello everyone! Data is required for every organisation in every field in today's world, and personal life. so, I am here to introduce how about What is Data and What is large scale computing.
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
The slide aids to understand and provide insights on the following topics,
* Overview for Data Science
* Definition of Data and Information
* Types of Data and Representation
* Data Value Chain - [ Data Acquisition; Data Analysis; Data Curating; Data Storage; Data Usage ]
* Basic concepts of Big Data
Data Science Innovations : Democratisation of Data and Data Science suresh sood
Data Science Innovations : Democratisation of Data and Data Science covers the opportunity of citizen data science lying at the convergence of natural language generation and discoveries in data made by the professions, not data scientists.
Machine learning applications nurturing growth of various business domainsShrutika Oswal
Machine learning is a science in which machines are becoming smarter and helping humans to make the best decisions based on previous data recommended practices. This technique is not new but is occupying fresh momentum. Machine Learning Algorithm learns from the previous records and analyses the data. Without any human interrupt, it will generate its own recommendation. A machine will add that recommendation as experience in its database and use it for further processing. In short, the machine learns from its own experience and gives you better and better output.
Machine learning is an iterative process as the more data added to machines learn from fresh feeds of data and then independently adapt new features to handle new data without constant human intervention. Machine learning was earlier used to predict what’s happing with the business but now the machine learning algorithm will suggest what action needs be taken by moving our business forward.
This PowerPoint presentation presents the results of a literature survey of machine learning applications nurturing the growth of various business domains. More specifically, it gives a brief introduction of Machine Learning, four major types of Machine Learning, enhancement in various business domains by the use of various machine learning algorithms.
This Thought Paper discusses how Artificial Intelligence could be used in the learning and development space. It provides various inspiration based on examples of solutions from and beyond the industry. The paper was prepared by Shweta Panwar and Debamitra Dasgupta within the Think Tank Center of Excellence of the Talent Development and Learning Practice in Accenture Capability Network.
SEAMLESS AUTOMATION AND INTEGRATION OF MACHINE LEARNING CAPABILITIES FOR BIG ...ijdpsjournal
The paper aims at proposing a solution for designing and developing a seamless automation and integration of machine learning capabilities for Big Data with the following requirements: 1) the ability to seamlessly handle and scale very large amount of unstructured and structured data from diversified and heterogeneous sources; 2) the ability to systematically determine the steps and procedures needed for
analyzing Big Data datasets based on data characteristics, domain expert inputs, and data pre-processing component; 3) the ability to automatically select the most appropriate libraries and tools to compute and accelerate the machine learning computations; and 4) the ability to perform Big Data analytics with high learning performance, but with minimal human intervention and supervision. The whole focus is to provide
a seamless automated and integrated solution which can be effectively used to analyze Big Data with highfrequency
and high-dimensional features from different types of data characteristics and different application problem domains, with high accuracy, robustness, and scalability. This paper highlights the research methodologies and research activities that we propose to be conducted by the Big Data researchers and practitioners in order to develop and support seamless automation and integration of machine learning capabilities for Big Data analytics.
Data Science is a form of science that focuses on dealing with huge chunks of data by using modern data analysis tools and techniques to discover hidden patterns, meaningful insights, and make critical business decisions.
A Data Science professional has to utilize complicated machine learning algorithms to develop predictive models. There could be multiple sources present in different formats used in data analysis.
Data Mining | How Organizations use Data Mining Techniques | Steps of Data Mining | Advantages and Disadvantages of Data Mining | Recommendation and Conclusion
Email : fahimbd329@gmail.com
LinkedIn : https://www.linkedin.com/in/md-wasiful-alam-fahim-709a84167/
Hello everyone! Data is required for every organisation in every field in today's world, and personal life. so, I am here to introduce how about What is Data and What is large scale computing.
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
The slide aids to understand and provide insights on the following topics,
* Overview for Data Science
* Definition of Data and Information
* Types of Data and Representation
* Data Value Chain - [ Data Acquisition; Data Analysis; Data Curating; Data Storage; Data Usage ]
* Basic concepts of Big Data
Data Science Innovations : Democratisation of Data and Data Science suresh sood
Data Science Innovations : Democratisation of Data and Data Science covers the opportunity of citizen data science lying at the convergence of natural language generation and discoveries in data made by the professions, not data scientists.
Machine learning applications nurturing growth of various business domainsShrutika Oswal
Machine learning is a science in which machines are becoming smarter and helping humans to make the best decisions based on previous data recommended practices. This technique is not new but is occupying fresh momentum. Machine Learning Algorithm learns from the previous records and analyses the data. Without any human interrupt, it will generate its own recommendation. A machine will add that recommendation as experience in its database and use it for further processing. In short, the machine learns from its own experience and gives you better and better output.
Machine learning is an iterative process as the more data added to machines learn from fresh feeds of data and then independently adapt new features to handle new data without constant human intervention. Machine learning was earlier used to predict what’s happing with the business but now the machine learning algorithm will suggest what action needs be taken by moving our business forward.
This PowerPoint presentation presents the results of a literature survey of machine learning applications nurturing the growth of various business domains. More specifically, it gives a brief introduction of Machine Learning, four major types of Machine Learning, enhancement in various business domains by the use of various machine learning algorithms.
This Thought Paper discusses how Artificial Intelligence could be used in the learning and development space. It provides various inspiration based on examples of solutions from and beyond the industry. The paper was prepared by Shweta Panwar and Debamitra Dasgupta within the Think Tank Center of Excellence of the Talent Development and Learning Practice in Accenture Capability Network.
App;ying Different Classification Technologies and for Different types of datasets such as Text and image dataset. Here I have used Machine learning and Deep Learning respectively for text and image datasets.
A quick guide to artificial intelligence working - TechaheadJatin Sapra
It is already on its way to achieving so as it has empowered the mobile app development agencies to build what was once assumed impossible. Despite this, much of this field remains undiscovered.
Object Automation Software Solutions Pvt Ltd in collaboration with SRM Ramapuram delivered Workshop for Skill Development on Artificial Intelligence.
Introduction to AI by Mr.Vaibhav Raja, Research Scholar from Object Automation.
The future of artificial intelligence in the workplaceONPASSIVE
Onpassive is the most advanced Artificial Intelligence-driven digital tool which helps any IT company to improve their outreach & productivity. It is an application that provides computer systems with the ability to learn and grow from experience without being explicitly programmed automatically.
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
Unlocking the Potential of Artificial Intelligence_ Machine Learning in Pract...eswaralaldevadoss
Machine learning is a subset of artificial intelligence that involves training computers to learn from data and make predictions or decisions based on that data. It involves building algorithms and models that can learn patterns and relationships from data and use that knowledge to make predictions or take actions.
Here are some key concepts that can help beginners understand machine learning:
Data: Machine learning algorithms require data to learn from. This data can come from a variety of sources such as databases, spreadsheets, or sensors. The quality and quantity of data can greatly impact the accuracy and effectiveness of machine learning models.
Training: In machine learning, training involves feeding data into a model and adjusting its parameters until it can accurately predict outcomes. This process involves testing and tweaking the model to improve its accuracy.
Algorithms: There are many different algorithms used in machine learning, each with its own strengths and weaknesses. Common machine learning algorithms include decision trees, random forests, and neural networks.
Supervised vs. Unsupervised Learning: Supervised learning involves training a model on labeled data, where the desired outcome is already known. Unsupervised learning, on the other hand, involves training a model on unlabeled data and allowing it to identify patterns and relationships on its own.
Evaluation: After training a model, it's important to evaluate its accuracy and performance on new data. This involves testing the model on a separate set of data that it hasn't seen before.
Overfitting vs. Underfitting: Overfitting occurs when a model is too complex and fits the training data too closely, leading to poor performance on new data. Underfitting occurs when a model is too simple and fails to capture important patterns in the data.
Applications: Machine learning is used in a wide range of applications, from predicting stock prices to identifying fraudulent transactions. It's important to understand the specific needs and constraints of each application when building machine learning models.
Overall, machine learning is a powerful tool that can help businesses and organizations make more informed decisions based on data. By understanding the basic concepts and techniques of machine learning, beginners can begin to explore the potential applications and benefits of this exciting field.
While machine learning is an exciting subject, it is wrong to assume that it will solve all your problems. Scroll down to take a look at some myths in the machine learning field and how to overcome them.
what-is-machine-learning-and-its-importance-in-todays-world.pdfTemok IT Services
Machine Learning is an AI method for teaching computers to learn from their mistakes. Machine learning algorithms can “learn” data directly from data without using an equation as a model by employing computational methods.
https://bit.ly/RightContactDataSpecialists
Public revenues and expenditures to GDP ratio
Public debt and %GDP, date of repayment
Structure of public sector – Central and Local gov., agencies
Budget revenues and their structure
Budget expenditures and their structure
Types of taxes (i.e. real estate tax)
Budget process
Budget presentation (classification)
It is all about Financial Analysis and Financial Statements. Also it contain some comparison of financial ratios to past, industry average, sector and firms.
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
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[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
Memorandum Of Association Constitution of Company.pptseri bangash
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
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Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
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As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
What are the main advantages of using HR recruiter services.pdfHumanResourceDimensi1
HR recruiter services offer top talents to companies according to their specific needs. They handle all recruitment tasks from job posting to onboarding and help companies concentrate on their business growth. With their expertise and years of experience, they streamline the hiring process and save time and resources for the company.
Tata Group Dials Taiwan for Its Chipmaking Ambition in Gujarat’s DholeraAvirahi City Dholera
The Tata Group, a titan of Indian industry, is making waves with its advanced talks with Taiwanese chipmakers Powerchip Semiconductor Manufacturing Corporation (PSMC) and UMC Group. The goal? Establishing a cutting-edge semiconductor fabrication unit (fab) in Dholera, Gujarat. This isn’t just any project; it’s a potential game changer for India’s chipmaking aspirations and a boon for investors seeking promising residential projects in dholera sir.
Visit : https://www.avirahi.com/blog/tata-group-dials-taiwan-for-its-chipmaking-ambition-in-gujarats-dholera/
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Artificial Intelligence
1. In Which Area AI is Used?
• This technology lets us accurately, unobtrusively and inexpensively collect wildlife data, which could help
catalyse the transformation of many fields of ecology, wildlife biology, zoology, conservation biology and
animal behaviour into 'big data' sciences. The information in these photographs is only useful once it has
been converted into text and numbers. Not only does the artificial intelligence system tell you which of 48
different species of animal is present, but it also tells you how many there are and what they are doing. It
will tell you if they are eating, sleeping, if babies are present, etc.
• More than 1 million Americans require daily physical assistance to get dressed because of injury, disease and
advanced age. Robots could potentially help, but cloth and the human body are complex.
• Computer scientists at Rice University have created a deep-learning, software-coding application that can
help human programmers navigate the growing multitude of often-undocumented application programming
interfaces. Bayou is a considerable improvement," he said. "A developer can give Bayou a very small amount
of information -- just a few keywords or prompts, really -- and Bayou will try to read the programmer's mind
and predict the program they want. Bayou is based on a method called neural sketch learning, which trains
an artificial neural network to recognize high-level patterns in hundreds of thousands of Java programs. It
does this by creating a "sketch" for each program it reads and then associating this sketch with the "intent"
that lies behind the program.
2. There are a number of areas where AI can be applied, including the
following:
Expert systems, where computers can be programmed to make decisions in real-life situations. The
integration of machines, software, and specific information allows the system to impart reasoning,
explanation, and advice to the end user.
Natural Language, where chatbots can recognize natural human language if communicating directly with a
user or a customer.
Neural Systems, simulate intelligence by attempting to reproduce the types of physical connections that
occur in human brains. For example, neural systems can predict future events based on historical data.
Robotics, are programmed computers which see, hear and react to sensory stimuli, such as light, heat,
temperature, sound and pressure.
Gaming Systems can manipulate strategic games, such as chess or poker, where the machine can think of an
exponential number of possible positions to play effectively against a human opponent.
3. 17 Everyday Applications of Artificial Intelligence in 2017
Smart Cars
Surveillance (Security Cameras)
Detecting fraud
Writing simple news stories (Fake News)
Customer Service
Video games
Predictive purchasing
Work automation and maintenance
prediction
Smart recommendations
Smart Homes
Virtual Assistants
Preventing heart attacks
Preserving Wildlife
Search and Rescue
Cybersecurity
Hiring (and perhaps firing)
4. An Example of ML -Netflix Pattern-
Measurable attributes gave Netflix the foundations to start analysing their
consumers and provide them with relevant and personalised content. Netflix’s
tagging system allows them to suggest and recommend other films and series’ they
think people will enjoy based on their previous viewing history. These suggestions
drive users to click and engage further with content.
Not only this, but thanks to targeted recommendations and advertising, Netflix has
been able to lower its promotional campaign budgets by being able to target only
the most relevant and valuable people at a time.
As of May 2018, Netflix has 125 million worldwide streaming subscribers. Having
this large user base allows Netflix to gather a tremendous amount of data. With
this data, Netflix can make better decisions and ultimately make users happier with
their service.
5. The goal of the technology is to stop recommending movies based on what you've seen,
and instead make suggestions based on what you actually like about your favourite
shows and movies.
That's why Netflix is moving into a field of research known as "deep learning." That
means that Netflix is "training" its software to provide better recommendations by
feeding massive amounts of information to a tech called "neural networks." Neural
networks mimic how the human brain identifies patterns.
The company took the lessons learned by researchers at Google, Stanford, and Nvidia
and created deep learning software that takes advantage of Amazon's powerful cloud
infrastructure, according to a new post on Netflix's technology blog.
Built upon a strong foundation of strategic decisions, Netflix has come a long way into
building a great learning model to predict what their users’ next favourite unwatched
movie could be, at a considerably high level of accuracy.
6. What's required to create good machine learning systems?
• Data preparation capabilities.
• Algorithms – basic and advanced.
• Automation and iterative processes.
• Scalability.
• Ensemble modelling.
Did you know?
• In machine learning, a target is called a label.
• In statistics, a target is called a dependent variable.
• A variable in statistics is called a feature in machine learning.
• A transformation in statistics is called feature creation in machine learning.
7. Machine Learning
• Supervised Machine Learning; The system uses past data to predict future outcomes.
For instance; classification of spam. The system is able to detect what characteristics an
email that`s spam or not spam exhibit. After learning this, it is able to categorize oncoming
emails as spam or otherwise.
• Unsupervised Machine Learning; Unsupervised learning only deals with the input data.
It basically work on the incoming data set to make it more readable and organized.
Basically, it analyses the input data to find out patterns or similarities or anomalies in
them.
For instance; Amazon take into consideration your prior purchases, and are able to suggest
other things that you may be interested in.
8. • Reinforcement Learning; Reinforcement Learning allows systems to learn based on past
rewards for its actions. Every time a system takes a decision, it is punished or rewarded
for it`s actions. For each action, it gets a feed back, with which it learns whether it
performed a wrong or correct action. This type of machine learning is strictly dedicated
to increase efficiency of a function/tool/program.
For instance; Let` s consider a game, say chess.
Determining the best moves would require a lot of research on numerous factors. Building
a machine designed to play such games would require a lot of rules to be specified. With
reinforced learning, we don`t have to deal with this problem, as the machine learns by
playing the game. It will make a move (decision), check if it`s the right move (feedback),
and keep the outcomes in mind for the next move it takes(learning).
9. How to Apply Machine Learning to Keyword Planner
When it comes to Keyword Difficulty or Organic Competition, no one really can accurately
predict the outcome as there are so many factors involved. It may even be difficult to
impossible for Google themselves to predict accurately beyond general guidelines and
suggestions.
For AdWords Competition or Paid Competition, having accurate data also will be important
because we will need to accurately plan and budget our SEM campaigns. Twinword Ideas is a
free keyword tool that gets its AdWords competition and CPC data directly from Google.
10. User journeys are complicated. It’s hard to give the correct “value” of a touchpoint early in
their journey.
Until AI surpasses general human intelligence, search advertising will always require some
degree of human involvement. For some campaigns, human control is needed at a far
more granular level.
This might be when an account lacks data, has a fluctuating or limited budget, or requires
personally chosen bid weightings on individual keywords.
11. How to Apply Machine Learning
to Keyword Planner
Searched word: Depilacja laserowa w pobliżu
So, instead of searching this word in AdWords and get
some ideas, it would be better for us to copy the links
of our competitors into AdWords and centralize these
keywords in excel.
Why we are doing this?
Rather than start creating a new keyword list, we can
take advantage of our competitors ` keywords. Our
competitors have already spent so much effort to
create this list, so we can get handy keywords from
them.
If we apply this transaction for the first 30 websites,
for instance, we will have;
• Various kind of keywords
• Keywords who can not be seen by others as long as
they do the same.
In short, `a big data` of keywords which is need to be
trimmed.
12. How we can do it! (Continued)
However, to do this we need to write a `script` to do it automatically (JavaScript). By doing this, our
boot will copy all these `URLs` (say top 30 ones) into a dossier and search every single of them in
AdWords to get different keywords.
At the end of this transaction, we will have a long keyword list which is need to be trimmed. So far,
we have received some help by boot, however from this point we, as human being, need to get
involved, and it requires personally chosen bid weightings on individual keywords.
Laser hair removal is such a huge sector that there are lots of keywords to be used. It is indeed that
there will be some keywords which are not related to laser hair removal, for this reason an
individual should get involved in to trim them.
Deleting poor keywords, we may use `Stanford Classifier` programme however, we need two kinds
of data:
• Trainer data
• Test data
13. Trainer Data;
A machine-learning algorithm is a mathematical model that learns to find
patterns in the input that is fed to it. This input is referred to as training data.
In this part we need to insert some data manually to teach the programme how to
classify the data steadyingly. The most frequently mistakes people have been
making, for instance, is to consider that IPL and Laser hair removal is the same
method.
So, in this stage, we may teach the programme how to classify the data, show
which keywords are useful and which one of them are not- and afterwards, the
programme may finally provide us a system to eliminate the
wrong/unappropriated/useless keywords as well as to promote nice/handy
keywords by using various algorithm.
Even if you want to classify your services for instance, laser for armpit, laser for face
or laser for feet, this classification will ensure you deeper insight into certain
objectives.
14. Test Data:
Once a machine learning algorithm learns the underlying patterns of the training
data, it needs to be tested on fresh data (or test data) that it has never seen before,
but which still belongs to the same distribution as the training data.
If our model performs well on the test data then it is considered as a ML model that
generalizes our dataset of interest.
15. Artificial Intelligence in Call centres
AI software has been developed that can listen to calls and decipher their impact on the customer,
such as how the issue was resolved, whether the customer’s loyalty will increase in the future as a
result of the call, and what could have been done to help smooth the situation if the customer gets
upset.
For instance; Singapore bank POSB has launched online chat functionality that understands and reacts
to its customers’ spoken language.
It is the latest bank to harness artificial intelligence (AI) to automate customer interactions with the
POSB digibank Virtual Assistant, which is available via Facebook Messenger.
By analysing, interpreting and understanding high volumes of customer inquiries, the solution could
support up-selling or cross-selling of various products or services, while the RPA robots could auto-fill
the application form to save the customer time.
Today’s digitally connected, always-on consumers demand unprecedented levels of 24x7x365
customer service
Chatbots can help reduce customer service costs by up to 40%
16. The vast amount of customer data and analytics being gathered means organizations have
the opportunity to understand each individual customer at a deeper level. For many
businesses, every customer touchpoint is captured digitally. With smart data analytics and
AI tools businesses can achieve a new standard of customer service, personalizing
communication and support based on the customer’s engagement to date. By creating a
more personally relevant experience for each customer, businesses can begin resolving
potential service issues or needs before they occur. After all, the better you know your
customer, the better you are able to anticipate their needs. With a comprehensive view of
all touchpoints, contact centres will be able to identify opportunities to proactively address
and/or eliminate reduce customer service issues.
• 57 percent of customer care executives consider call reduction their top priority for the
next five years.
• According to IBM, 70 percent of customers would prefer using messaging over voice for
customer service when given the choice.
17. Voice is the most used communication channel for service. Voice, which 73% of customers use for
customer service, is still the most widely used channel. However, web self-service and digital channels
like chat and email are following close behind.
For example, according to George, "80% of the calls an airline receives to change a ticket do not result in
the ticket changing," because the person may not efficiently be made aware of all of the terms and
conditions involved, such as change fees or scheduling issues. The AI system can quickly provide this
pertinent and relevant information to the caller, without engaging the services of a live agent. "By using
bots, customer call volume can be reduced [significantly].“
RECOMMENDATION
By looking these info and examples, we can create our own AI for call centre department at least when
our employees are not at office.
Firstly, it can seamlessly give customers the right information they need at the right time by offering
self-service options, eliminating the need for a call to customer service.
Second, AI has the potential to give customer service representatives more information to help them
handle the complicated issues that self-service cannot resolve.
In addition, with AI technology, the more it gets used, the more it learns, meaning that it grows ever
more sophisticated. This capability makes it ideal for everyday IT processes like password resets.
18. RECOMMENDATION
We should built a nice website which
demonstrate a whole body of human being.
Lets say a customer clicked on `chest` to see
the information that have is located, like how
much it will cost and how many treatments
she/he needs.
With this click, we can deduce that this
customer needs a treatment for this part and
we can directly target this customer via phone
calls, massages, e-mails.
Even if they do not click, it is important that
where they are holding the mouse on the
screen. In this way, we can guess their
intentions.
This Strategy is used by bigger companies like
amazon and e-bay, so why we not?
Editor's Notes
While they’re rather simple when compared to other AI systems, apps like Spotify, Pandora, and Netflix accomplish a useful task: recommending music and movies based on the interests you’ve expressed and judgments you’ve made in the past. By monitoring the choices you make and inserting them into a learning algorithm, these apps make recommendations that you’re likely to be interested in.