Study Skills for Higher Education: Deep Learning Analysis Report

This report delves into the concept of deep learning, a machine learning method inspired by artificial neural networks, and its crucial role in higher education. It emphasizes the importance of deep learning for students, highlighting its ability to foster critical thinking, problem-solving skills, and collaborative work. The report analyzes the development of deep learning, illustrating its application across different educational levels and its focus on promoting analysis, interpretation, and the ability to make connections between ideas. The report concludes that deep learning is essential for students to develop analytical skills and participate in authentic work experiences, preparing them for success in today's world. The report also references several key publications on deep learning, providing a comprehensive overview of the topic and its significance for the student year foundation.

Study Skills for higher
education

Table of Contents
INTRODUCTION ..........................................................................................................................1
Discuss the concept of deep learning and identify it's importance for the student year
foundation ..................................................................................................................................1
Explain how deep learning is developed ...................................................................................2
Draw conclusions based on key points .....................................................................................3
REFERENCES................................................................................................................................4
.........................................................................................................................................................4

INTRODUCTION
Deep learning is defined a the machine learning method which is based on artificial
neural networks. It is important to supervise, unsupervised and supervised the learning. There are
various architectures of deep learning like deep belief networks, deep neural networks and
convolutional neural networks. The following report includes discussion on concept of deep
learning and it's importance for student year foundation. The development of deep learning is
analysed and conclusions are made for this.
Discuss the concept of deep learning and identify it's importance for the student year foundation
Deep learning is defined as function of artificial intelligence which imitates the working
of human brain in data processing and creation of patterns in order to use in decision making
process. This is a subset of machine learning in artificial intelligence which has networks that is
capable of learning unsupervised from data which is unlabelled and unstructured
(Bengio,Goodfellow and Courville, 2017). This is also known as deep neural network and deep
neural learning. Deep learning is a machine learning technique which guides computers to act
like human beings. This is a key technology used in driverless cars which is used in recognising
a stop sign and distinguishing a pedestrian from a lamppost. This is a technique which is used in
different devices such as tablets, phones, hands free speakers, television and laptops. This has
helped in making life easier and achieving results that were not possible before. The deep
learning knowledge, competencies and abilities are essential for working, living and becoming a
good citizen. This is helpful in promoting the qualities that children require for success. This is
done by building more understanding and meaning. The instructions of deep learning provides
necessary advanced skills needed by students. The main objective of students is to build their
career and find a good job. Deep learning helps students to become curious, independent learners
and also being productive and thoughtful in democratic society. The deep learning teachers are
very effective for making students more smart and creative. When students are taught by deep
learning it means making significant efforts for deep understanding of concept and skill
development. Students are engaged in deep learning processes and this provides great
opportunity to them for asking questions, constructing meaning and learning from other people.
Students are able to make alternatives solutions for problems and it becomes easy to apply ideas,
skills and key concepts to advanced understanding and critical thinking. The deep learning
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process for students is more thoughtful, proactive and collaborative (Goodfellow, Bengio and
Courville, 2016). In this process, students are given opportunities for applying to learn authentic
situations which build deep learning skills and understanding, promoting critical habits of mind,
developing curiosity and interest, etc.
Explain how deep learning is developed
The deep learning teaching method or process is found in all levels of learning and
different types of school programs. This can be explained with an example in case of early
childhood, deep learning includes reading chapters for students, summarising new ideas and
learning information from a non fiction portion or literature review. This also consist of raising
meaningful literature, interpretation, open ended questions and analysis of information. In case
of high schools, teachers can make students to read six or seven books a year (Hoffer and Ailon,
2015). After this reading of books understanding of literature is developed, story and vocabulary
of each book is analysed. Students are asked questions for developing analysis and
interpretations of books. This is done through research, open ended questions, projects and
written reflections. In context of middle school, teachers teach different topics in great depth and
considerable time is spend helping students for conceptualising key ideas, understanding nature
and goals of scientific methods. This includes conducting experiments with students and
implementing actual projects that are needed by students for applying science learning to new
situations. History teachers may use necessary questions and understanding for focusing on
convention and asking students to use what has been learned for analysing and understanding
present issues and challenges. Teachers can also provide basic information. Simple problems,
vocabulary, so that student is able to build skills and abilities. The deep learning process method
is less focusing on teaching different topics and giving a breadth of information. This process
focuses on understanding and making connections for building relationships among ideas and
informations. The main emphasis is on promoting analysis, application and interpretation.
Students have various opportunities for processing ideas and information as they develop and use
thinking skills and literacy skills. Students are engaged in learning process and they are less
passive. Students are taught to learn real life situations that are helpful for him in the long run. It
is concluded that deep learning method is a perfect way to build abilities and skills among
students. Schools of different countries have started adopting this technique from the initial level
of teaching as this helps to make creative and talented students. It is responsibility of schools to
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provide deep learning methods to students in order to provide them effective understanding and
learning. Deep learning processes provides a meaningful open ended questions that forms a basis
of learning. Students who are actively using deep learning can construct meaning and processing
ideas and information (Lenz,Lee and Saxena, 2015). Students have to use their intellect for
understanding basic principles and ideas, analysing and interpreting this basic learning by a new
experience. Students have to fully engage in authentic experience which is helpful in deepening
understanding and developing cognitive complex learning skills and habits.
Draw conclusions based on key points
From the above discussion, it is concluded that deep learning is very effective for
students as it helps in developing skills and abilities. There are a number of assessment methods
and instructional approaches which engages students. This allows student for developing critical
thinking and solving complex problems. Students learn to collaboratively work, incorporate
feedback, communicate appropriately and develop academic mindset which are necessary for
directing learning. In the deep learning process, students have the ability to enhance their
knowledge and skill and investigating a meaningful problem. This helps them to answer complex
problem. Project in context of real life are executed for developing great understanding among
students about the topic (LeCun, Bengio & Hinton, 2015)(Schmidhuber, 2015). Students share
their thoughts and project work to other classmates which explains, presents and displays a great
understanding of research topic. Students can apply knowledge and classroom content in real
world by maintaining clear connection between work and school. Deep learning process is
applied to students with academic instructions and preparation of content. In today's world
employers are searching for individuals who have analytical skills and knowledge. Thus deep
learning is essential in students as it prepares them to participate in authentic work experiences
and developing skills and habits like critical thinking, collaboration and problem solving.
Instructional approaches of deep learning are measures a wide range of knowledge and skills
which provides students to develop their knowledge. In deep learning, students have an
opportunity to demonstrate their learning by various methods and modalities which appeal to
multiple interests and styles. The assessing of students by this approach means going beyond
essays, multiple choice tests, short answer exam and presentations. Deep learning is defined as
method for dealing with higher order thinking and emphasising the ability of learners to
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understand content of learning and building relationships between new and old knowledge for
solving practical problems.
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REFERENCES
Books and Journals
Bengio, Y., Goodfellow, I. and Courville, A., 2017. Deep learning (Vol. 1). MIT press.
Goodfellow, I., Bengio, Y. and Courville, A., 2016. Deep learning. MIT press.
Hoffer, E. and Ailon, N., 2015, October. Deep metric learning using triplet network.
In International Workshop on Similarity-Based Pattern Recognition (pp. 84-92).
Springer, Cham.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436.
Lenz, I., Lee, H. and Saxena, A., 2015. Deep learning for detecting robotic grasps. The
International Journal of Robotics Research, 34(4-5), pp.705-724.
Schmidhuber, J., 2015. Deep learning in neural networks: An overview. Neural networks, 61,
pp.85-117.
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