Code With MEMO

You're processing an infinite stream of numbers and need to continuously maintain the median. You cannot store all numbers due to memory constraints. What data structures and algorithms would you use, and how would they scale?

🔰 JavaScript Decorators & Annotations

Decorators enable metaprogramming by extending classes/methods at design time.

This two neural network platforms⚡️

It's Day 4 Unlocked Day 4: Data Fundamentals Importance of data in AI Data types: numerical, categorical, text Basic data preprocessing Introduction to Pandas

Every year, a massive amount of CO2 is emitted from electricity generation worldwide. To reduce CO 2 emissions and plan our energy strategy accordingly, it is essential to gather an idea about future CO2 emissions. Therefore, develop a 10-year CO2 emission forecasting model. The dataset and its description are available here: https://www.kaggle.com/datasets/txtrouble/carbon-emissions.

GM

Day 3: Platforms for Practice Introduction to Google Colab, Kaggle Jupyter Notebook basics GitHub for AI projects

GM

Up to next ...... Stay with me @codewithmemo

Brain storming Questions after Day 2: 1. How are input data handled before implementing ML algorithms? Mention the steps. 2. Why is data augmentation required, and how is it implemented? 3. The datasets often contain missing data. How can this problem be addressed? 4. What do stationary and non-stationary time series signify? Differentiate between them using an example. 5. Why do we need different types of ML algorithms? Briefly discuss. 6. Discuss the relationship between deep learning and neural networks. What are the advantages of deep learning methods?

it's time to make it Happen. consistency is the key.