Editorial
I Artificial Intelligence and Machine Learning
1 Data Driven learning
1.1 Data
1.2 5Vs of Big Data
1.3 Significance of Data in Machine Learning
1.4 Types of Data
1.5 Generating data using GAN
1.6 Data for ChatGPT
1.7 Conclusion
2 Machines that can understand Human Languages
2.1 Lexical Analysis
2.2 Syntactic analysis
2.3 Semantic Analysis
2.4 Disclosure Integration
2.5 Pragmatic analysis
3 AI over a Coffee
3.1 The dumb and powerful computers of the past
3.2 New-Age computers that can learn
3.3 A.I. in science and engineering
3.4 Primitive learning algorithms
3.5 Artificial Neural Networks
II Astronomy and Astrophysics
1 Applications of Satellite Imaging
1.1 Use cases of Satellite imaging
1.2 Challenges
2 Eclipsing Binaries Part- 2
2.1 Introduction
2.2 Classification according to the physical characteristics of the components
2.3 Classification based on the degree of filling of inner Roche lobes
2.4 Some examples of Eclipsing binaries
III Biosciences
1 An introduction to Molecular Biology
1.1 Central Dogma
1.2 How does the Gene expression connected to the Central Dogma of Molecular Biology?
IV Computer Programming
1 Remote Sensing and Artificial Intelligence in Agriculture
V Fiction
1 Curves and Curved Trajectories