---
# System prepended metadata

title: DSG Open Community Resources
tags: [Documentation, Templates]

---

---
title: 'DSG Open Community Resources'
disqus: hackmd
---

Comprehensive AI/ML + Maths Resources
===

Hello everyone, DSG is launching a resource-sharing gig to sprinkle some ML and DL magic into your lives! 
Whether you aced the recruitment process or missed out, everyone's invited to hop on this knowledge train!


## Mathematical Foundation

Before delving into Machine Learning and Deep Learning, it's crucial to solidify the mathematical foundations upon which these fields are built. Mathematics is the backbone of ML and DL algorithms, and a strong grasp of key concepts like probability, statistics, linear algebra, and optimization is essential. This section equips you with those foundational skills. 
#### Resources

[Prob-Stats 1 ](https://hackmd.io/@eMS9nZq5Tk6-gP09chWyqQ/H1TZcit6a) : Begin with the basics of probability and statistics, which will help you understand data distribution, uncertainty, and decision-making processes—key elements in building ML models.
[Prob-Stats 2](https://hackmd.io/@ZXxKhF68QyCRN3u4US17ZQ/ryAOaL_0a
) : This further explores probability and statistics, diving deeper into advanced topics that are critical in more complex ML models, such as Bayesian inference and hypothesis testing.
[Linear Algebra and Optimisation](https://hackmd.io/CRuXzA0XRFy5I2Yh51dODg?view
) : Linear algebra forms the foundation for many ML algorithms, particularly in deep learning where operations on high-dimensional data are frequent. Optimization is the process of improving these models, and understanding both is indispensable for tackling real-world ML problems.
#### Assignments

[Prob-Stats 1 ](https://hackmd.io/Id8UgDukSImYiMI3tDKPkQ?view
)
[Prob-Stats 2](https://drive.google.com/file/d/1pZ4H1ZvW_c12bXdQzIadp-s7HW9BI7OF/view?usp=drive_link
)
[Linear Algebra and Optimisation](https://drive.google.com/file/d/1wYamT_XjATDna4iI9bgSFfliuf4kwZ9U/view?usp=sharing)


## Machine Learning
After you are over with all the math resources and assignments, with the mathematical foundations firmly in place, we urge you to move on to the core subject of our journey: Machine Learning. It’s essential to understand both the theory and application of ML algorithms to build systems that solve complex problems.

#### Resources

[ML-0](https://hackmd.io/@aakashks/B1iicQnlA)
[ML-1](https://hackmd.io/@tisanant/ry5AjOxX0)

#### Assignments

[ML-0](https://hackmd.io/@aakashks/BJvKgy2zC)
For ML-1, we will hold a hackathon later this year in place of the assignment. Until then, happy learning!


## Deep Learning
Moving on to Deep Learning, a subset of machine learning that focuses on models known as neural networks. This section will deepen your understanding of the cutting-edge techniques driving today’s AI breakthroughs.

[Resources](https://hackmd.io/@bo1tKdKHTzWAvzZH0oC_SA/SJL_JDjQ0)
[Assignment](https://hackmd.io/@0xpegasus/ryXpSJ8E0)

With these resources and assignments, you’re well on your journey to discovering and understanding AI/ML. This will serve as the last assignment for now, we hope you had a good experience learning from these resources and assignments!
