Data Science

Data science is an interdisciplinary field that utilizes scientific methods, algorithms, and systems to analyze and interpret complex data, combining computer science, statistics, mathematics, and domain expertise.

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Topics to be covered

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Introduction to Data Science

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Data Collection and Cleaning

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Data Exploration and Visualization

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Data Manipulation and Analysis

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Machine Learning Basics

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Supervised Learning Algorithms

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Unsupervised Learning Algorithms

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Model Selection and Evaluation

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Natural Language Processing (NLP)

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Time Series Analysis

Swiggy launches new service Bolt to deliver food in 10-15 minutes

#66

December 27, 2024

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Editor’s Note:

Tech buffet alert! Today’s edition is packed with delicious bites."! From Swiggy's lightning-fast Bolt delivery to the AI skills frenzy gripping developers, there's something for everyone. And if you're hungry for more, our curated list of machine learning books will satisfy your cravings for knowledge. So, grab a seat, fasten your seatbelt, and let's dive into the world of tech innovation!

Swiggy launches new service Bolt to deliver food in 10-15 minutes

Public markets-bound Swiggy has rolled out a 10-minute food delivery service Bolt, the company said. Under Bolt, Swiggy is offering deliveries of a limited set of items from select restaurants that will be delivered within 10 to 15 minutes.

How Melissa’s Global Phone service cuts down on data errors and saves companies money

Having the correct customer information in your databases is necessary for a number of reasons, but especially when it comes to active contact information like email addresses or phone numbers. Learn how “Global Phone” allows customers the ability to standardise and validate phone numbers, to correct and detect any issues that may be present.

80% of developers need to upgrade their skills by 2027

Generative AI will place new demands on developers in the coming years, according to a recent report by research firm Gartner, which found in a survey of 300 organisations in the US and UK late last year that 56% viewed developers with skills in AI and machine learning as the most in-demand role in 2024.

Analog Devices Launches Embedded Software Development Environment

Analog Devices, a global semiconductor leader, launched a suite of developer-centric offerings that unite cross-device, cross- market hardware, software and services to help customers deliver innovations for the Intelligent Edge with enhanced speed and security.

Resource Spotlight:

Books

  • Machine Learning for Mortals (Mere and Otherwise) - Early access book that provides basics of machine learning and using R programming language.

  • How Machine Learning Works - Mostafa Samir. Early access book that introduces machine learning from both practical and theoretical aspects in a non-threatening way.

  • MachineLearningWithTensorFlow2ed is a book on general-purpose machine learning techniques, including regression, classification, unsupervised clustering, reinforcement learning, autoencoders, convolutional neural networks, RNNs, and LSTMs, using TensorFlow 1.14.1.

  • Serverless Machine Learning - a book for machine learning engineers on how to train and deploy machine learning systems on public clouds like AWS, Azure, and GCP, using a code-oriented approach.

  • The Hundred-Page Machine Learning Book - all you need to know about Machine Learning in a hundred pages, supervised and unsupervised learning, SVM, neural networks, ensemble methods, gradient descent, cluster analysis and dimensionality reduction, autoencoders and transfer learning, feature engineering and hyperparameter tuning.

  • Trust in Machine Learning - a book for experienced data scientists and machine learning engineers on how to make your AI a trustworthy partner. Build machine learning systems that are explainable, robust, transparent, and optimized for fairness.

  • Generative AI in Action - A book that shows exactly how to add generative AI tools for text, images, and code, and more into your organization’s strategies and projects.

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