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INSIDE THE SERIES
The key features of the series have been designed to ensure better
learning and assessment. S teps f or Ef f ective T ime Manag ement
Following steps help in effective time management:
Learning Resources 1. Set goals
correctly
UNIT-1 7. Plan ahead 2. Prioritize
wisely
COMMUNICATION SKILLS-I
Learning Outcomes: 6. Time Management
Remove non Tips
3. Set a
It provides an overview of the essential time limit At a Glance:
tasks
unit/chapter contents. This section provides a summary
4. Take
5. Organize
yourself breaks
between of the chapter.
tasks
Learning Outcomes
• What is Communication? • Perspectives in Communication At a Glance
• Factors Affecting Perspectives in Communication • Effective ways of Communication
• Types of Communication • 3P’s of Public Speaking • Analysing your strengths and weaknesses is helpful.
• Writing Skills • Phrases • An analysis of strengths and eaknesses begins ith kno ing and understanding yourself first.
• What is a Sentence? • Construction of a Paragraph Values are the principles or standards of action; your own judgment about what is important in your life.
• Parts of Speech • Use of Articles •
• When no Articles are used • Knowing ‘yourself’ means you understand who you are, what you like or do not like, what your beliefs or
opinions are, what is your background, what you are good or bad at.
Communication is an age old method to convey any information effectively. In this unit, we will discuss different • Strength or ability is what you do well and are good at.
ways of communication which is very useful for a student to learn. If a person has good communication skills, then, • Weakness, also known as "area for improvement" is what you don't do well and what you're not good at.
it becomes easy to convey a message in short and simple sentences. This develops confidence and helps a person • Grooming is the process of giving oneself a neat, orderly and clean appearance.
survive in the vast ocean of Information Technology (IT). • he ay you dress and groom can send a message that you are a confident and smart person.
• Personal hygiene is the habit or practice of keeping clean.
What is Communication? • Cleanliness helps us maintain our health and spirit.
• A team is a group of people who work together to achieve a common goal.
The word ‘communication’ is derived from the Latin word communicare, meaning “to share”. It is defined as a way of
AI Glossary: • Networking means getting to know people, staying in touch over time and using knowledge or skills to
conveying a meaningful message from one entity to another in the form of signs, symbols, behaviour using verbal
help each other.
and non-verbal skills. It is important that whatever we want to communicate is conveyed effectively. • Self-motivation is what drives us to achieve our goals, makes us feel happy and improve the quality of
This section contains definitions our lives.
Elements of C ommunication
Communication is the process of transmission
of important AI terms. Feedback Sender • • Goals are a set of dreams with an achievable deadline.
oal setting is finding and listing your goals and then planning ho to achieve them.
of an appropriate message from a sender to
a receiver through a transmission channel in • Time management is the ability to plan and control how you spend your time well and do whatever you
a proper format. The communication process Decoding Ideas/Message want.
helps in sharing of a common meaning
Elements of
between the sender and the receiver. Let us Communication S e lf - M an ag e m e n t S k i lls- III 4 7
study all these elements in detail.
• Sender: Can be any person, group or an
organisation that initiates the process of Receiver Encoding
communication. The sender’s knowledge,
F Chatbot: It is an AI application Communication
experiences and skills influence the quality that can mimic a real conversation ith a user in their natural
language.
of the message. Channel Video Session:
C om m uni cati on S k i l l s- I
19
F Natural Language Processing (NLP): It is an area of artificial intelligence that employs natural This section contains a link of the
language for interaction bet een computers and humans.
video related to the topic for better
F Sentiment Analysis: It is also called Opinion ining or motion AI, uses to determine Brainy Fact
hether data is positive, negative, or neutral. Contrary to popular belief, one of the early adopters of ML is Israel (63%) followed by Netherlands (57%)
understanding of the concept.
and then United States (56%). (Business Broadway Survey, February 2021)
F Cognitive Computing: It refers to individual technologies that perform specific tasks to enable
human intelligence.
Evaluation
F Deep Learning: It is a subset of machine learning based on neural net orks that permit a machine Once a model has been created and trained, it must be properly tested to calculate the model's efficiency and
to train itself to perform a task. performance. As a result, the model is evaluated using Testing Data (which was extracted from the acquired dataset
during the Data Acquisition stage) and the model's efficiency is assessed.
F Machine Learning: It is a subset of AI that includes techniques that enable machines to improve The set of measurements will differ depending on the problem you're working on. For regression problems, for
at performing tasks ith e perience. example, MSE or MAE are commonly used. On the other hand, for a balanced dataset, accuracy may be a useful
choice for evaluating a classification model. Imbalanced sets necessitate the use of more advanced metrics. In such
S
F tructured Data: It is the type of data hich e interact and ork ith every day. instances, the F1 score is useful.
A separate validation dataset is used for evaluation during training. It monitors how well our model generalises,
F Unstructured Data: It is the type of data hich neither possesses any fi ed data type nor the si e avoiding bias and overfitting.
is fi ed.
AI Innovators: There are a few other things considered during this stage too:
The volume of test data can be huge, which provides data complexities.
•
R
F elational Algebra: It is a set of algebraic operators and rules used to manipulate relational
It presents information about the • Human biases in picking test data might have a negative impact on the testing phase; thus, data validation is
tables to generate the required information.
critical.
pioneers in the field of AI. • The testing team should put the AI and ML algorithms through rigorous testing while maintaining model
F AI Bias: It is a phenomenon hich occurs hen algorithm results are systematically biased against
a certain gender, language, race, ealth, etc. validity and keeping successful learnability, and algorithm efficacy in mind.
Brainy Fact:
• As the system may deal with sensitive data, regulatory compliance and security testing are essential.
F Conflict: It can be defined as a clash bet een t o opposing forces that creates the narrative • Also, due to the sheer volume of data, performance testing is critical.
It presents an interesting fact relevant
thread for a story. • If the AI solution requires data from other systems, systems integration testing is critical.
• All relevant subsets of training data, i.e., the data you will use to train the AI system, should be included in test
to the topic of the chapters.
F Design Thinking: It is a process to solve problems creatively by putting consumers' needs first. data.
• The team involved in testing must develop test suites to aid in the validation of the ML models.
Gazal S. Kalra
F egression: It is a achine earning algorithm used to analyse the relationship among dependent
R
target) and independent predictor) variables.
In urgaon, ivigo ervices vt td, a logistics
business, a al . alra is one of the company's
F Correlation: It is a statistical method that indicates hether a pair of variables has a linear Brainy Fact
co founders. In addition to being an II Delhi
relationship and ill change together. Training Dataset vs Test Dataset vs Validation Dataset
alumnus, a al has an A from tanford niversity The training dataset is the set of data that was utilised to fit the model.
F Clustering: It is an unsupervised machine learning technique that automatically divides the data
raduate chool of usiness and a aster of ublic
into clusters or groups of similar elements. Validation Dataset: A subset of data used to offer an unbiased evaluation of a model's fit on the training
Administration from arvard ennedy chool of
dataset while tuning model hyperparameters. As proficiency of the validation dataset is incorporated into
overnment. AI Glossary the model setup, the evaluation becomes increasingly biased.
ivigo as established by a al in because she 327 The sample of data used to offer an unbiased evaluation of a final model fit on the training dataset is referred
Gazal S. Kalra to as the test dataset. The test data set is sometimes known as a holdout data set if the data in it has never
en oys creating meaningful, inventive, and scalable been used in training (for example, in cross-validation).
enterprises. he startup ants to revolutionise the logistics industry by offering its customers
dependable, precise delivery timeframes.
very pilot and truck driver received ample time to spend ith their families thanks to the Phase III: Deployment and Maintenance
service model designed by a al and her team. hey can also live a life of respect and dignity. Phase III is divided into two stages: Deployment and Feedback. Let us discuss about them in detail.
Model Lifecycle 133
Andrej Karpathy
enior Director of Artificial Intelligence at esla,
Andre arpathy leads the team orking
on neural net orks of Autopilot in esla s
cars. e orked previously at OpenAI as
a research scientist on Deep earning in
omputer vision, einforcement earning and
enerative odeling. Andre orked ith
ei ei i for his h.D at tanford, here he
orked on onvolutional ecurrent eural
Andrej Karpathy et ork architectures and their applications
in atural anguage rocessing and omputer
ision and their intersection. e also interned at oogle orking on large scale feature
learning over ou ube videos.
240 Touchpad Artificial Intelligence (Ver. 2.0)-XII AI Innovators 240

