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Commonly used Python libraries are:

👉🏻NumPy: This library is used for scientific computing and working with arrays of data. It provides functions for working with arrays of data, including mathematical operations, linear algebra, and random number generation.

👉🏻Pandas: This library is used for data manipulation and analysis. It provides tools for importing, cleaning, and transforming data, as well as tools for working with time series data and performing statistical analysis.

👉🏻Matplotlib: This library is used for data visualization. It provides functions for creating a wide range of plots, including scatter plots, line plots, bar plots, and histograms.

👉🏻Scikit-learn: This library is used for machine learning. It provides a range of algorithms for classification, regression, clustering, and dimensionality reduction, as well as tools for model evaluation and selection.

👉🏻TensorFlow: This library is used for deep learning. It provides a range of tools and libraries for building and training neural networks, including support for distributed training and hardware acceleration.

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Commonly used Python libraries are:

👉🏻NumPy: This library is used for scientific computing and working with arrays of data. It provides functions for working with arrays of data, including mathematical operations, linear algebra, and random number generation.

👉🏻Pandas: This library is used for data manipulation and analysis. It provides tools for importing, cleaning, and transforming data, as well as tools for working with time series data and performing statistical analysis.

👉🏻Matplotlib: This library is used for data visualization. It provides functions for creating a wide range of plots, including scatter plots, line plots, bar plots, and histograms.

👉🏻Scikit-learn: This library is used for machine learning. It provides a range of algorithms for classification, regression, clustering, and dimensionality reduction, as well as tools for model evaluation and selection.

👉🏻TensorFlow: This library is used for deep learning. It provides a range of tools and libraries for building and training neural networks, including support for distributed training and hardware acceleration.

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Telegram hopes to raise $1bn with a convertible bond private placement

The super secure UAE-based Telegram messenger service, developed by Russian-born software icon Pavel Durov, is looking to raise $1bn through a bond placement to a limited number of investors from Russia, Europe, Asia and the Middle East, the Kommersant daily reported citing unnamed sources on February 18, 2021.The issue reportedly comprises exchange bonds that could be converted into equity in the messaging service that is currently 100% owned by Durov and his brother Nikolai.Kommersant reports that the price of the conversion would be at a 10% discount to a potential IPO should it happen within five years.The minimum bond placement is said to be set at $50mn, but could be lowered to $10mn. Five-year bonds could carry an annual coupon of 7-8%.

Importantly, that investor viewpoint is not new. It cycles in when conditions are right (and vice versa). It also brings the ineffective warnings of an overpriced market with it.Looking toward a good 2022 stock market, there is no apparent reason to expect these issues to change.

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Commonly used Python libraries are:👉🏻NumPy: This library is used for scientific computing and working with arrays of data. It provides functions for working with arrays of data

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