Two sentences are given—“The men are playing soccer on the beach” and “The
boys are playing soccer near the beach.” Write Python program(s) to determine
cosine similarity and Jaccard similarity. Do these distance metrics agree?
boys are playing soccer near the beach.” Write Python program(s) to determine
cosine similarity and Jaccard similarity. Do these distance metrics agree?
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Mebrie
You can do like this
we can make conclusion like: the two sentences are related according to cosine similarity result
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?
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?
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Day 3: Platforms for Practice
Introduction to Google Colab, Kaggle
Jupyter Notebook basics
GitHub for AI projects
Introduction to Google Colab, Kaggle
Jupyter Notebook basics
GitHub for AI projects
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Code With MEMO pinned «Day 3: Platforms for Practice Introduction to Google Colab, Kaggle Jupyter Notebook basics GitHub for AI projects»
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.
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.
Kaggle
Carbon Emissions
Carbon emissions from electicity production
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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
Importance of data in AI
Data types: numerical, categorical, text
Basic data preprocessing
Introduction to Pandas
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