The document outlines a session on vector and matrix operations, including vector operations, vector-vector multiplication, matrix-vector multiplication, matrix-matrix multiplication, and computing the matrix inverse. It provides examples of performing these operations on vectors and matrices.
ML Zoomcamp 1.3 - Supervised Machine LearningAlexey Grigorev
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The document discusses supervised machine learning. It defines supervised machine learning and provides examples of regression, classification, and ranking problems. It also includes examples of datasets with features and target values for classification and regression problems. Machine learning algorithms are trained on these labeled examples to learn a function that maps new examples to output labels.
ML Zoomcamp 2.1 - Car Price Prediction ProjectAlexey Grigorev
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This document outlines the plan for a car price prediction project. The plan includes preparing and exploring the data, using linear regression to predict prices, understanding how linear regression works, evaluating the model's accuracy, engineering features, regularizing the model, and implementing the model. The source code for the project is available at a GitHub link provided. The next step mentioned is exploratory data analysis of the data.
This document outlines the course plan for a Machine Learning zoom camp hosted by DataTalks.Club. The 11-session course will cover topics ranging from introductory machine learning concepts to advanced techniques like deep learning, model deployment, and Kubernetes. Participants should have some Python experience and be comfortable with command line. Completing homework assignments and projects can earn participants up to 100 points to be listed on a public leaderboard. The goal is to help attendees learn applied machine learning skills in a collaborative, public setting.
The document discusses the process of selecting the best machine learning model, including evaluating multiple models on a holdout dataset to determine the best performing one. It notes common model types like logistic regression, decision trees, and neural networks that could be considered. It also addresses the need to split data into training, validation, and test sets to accurately assess model performance and avoid overfitting conclusions from multiple comparisons of models during selection.
3rd issue of Volume 8. A magazine in urdu language mainly based on spiritual treatment and learning. Many topics on ISLAM, SUFISM, SOCIAL PROBLEMS, SELF HELP, PSYCHOLOGY, HEALTH, SPIRITUAL TREATMENT etc. A Very useful magazine for everyone.
Zs 0992 teks viler dolina vukova (scanturion & zikateror & emeri)(5...zoran radovic
油
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to boost self-esteem and can serve as a healthy way to manage stress.
The document discusses the history and development of chocolate over centuries. It details how cocoa beans were first used by Mesoamerican cultures before being introduced to Europe. Chocolate then evolved from a luxury good to a mass-produced confection as production methods advanced and it became commercially available on a larger scale.
Zs 0995 zagor - zakon predaka (scanturion & enwil & quaresma & ...zoran radovic
油
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to boost self-esteem and can serve as a healthy way to manage stress.
This document contains summaries from multiple sessions of a machine learning zoomcamp. It introduces machine learning concepts like supervised learning, the CRISP-DM process, model selection, linear algebra, and the Python libraries NumPy and Pandas. It also discusses setting up an environment for machine learning and provides example data and models for tasks like email spam detection and car price prediction.
The document discusses the benefits of exercise for both physical and mental health. Regular exercise can improve cardiovascular health, reduce stress and anxiety, boost mood, and reduce the risk of diseases. The effects of exercise are wide-ranging and even a modest routine can lead to significant health improvements.
Docfoc.com dok holidej 003 - frenk larami - pakleni poker (matorimikica &...zoran radovic
油
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to increase gray matter volume in the brain and reduce risks for conditions like Alzheimer's and dementia.
The document discusses the benefits of exercise for mental health. It notes that regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise has also been shown to enhance self-esteem and quality of life.
This document summarizes a presentation about data science at OLX. It discusses OLX's moderation and recommender systems. For moderation, it describes OLX's machine learning models that automatically moderate listings for issues like duplicates, spam, and illegal/NSFW content. Moderators review flagged content. For recommendations, it discusses collaborative filtering and item embeddings to suggest relevant listings to users. It also outlines OLX's team structure, goal setting process, and expectations for data scientists, which include a focus on modeling, evaluation and some production work.
This document outlines the course plan for a Machine Learning zoom camp hosted by DataTalks.Club. The 11-session course will cover topics ranging from introductory machine learning concepts to advanced techniques like deep learning, model deployment, and Kubernetes. Participants should have some Python experience and be comfortable with command line. Completing homework assignments and projects can earn participants up to 100 points to be listed on a public leaderboard. The goal is to help attendees learn applied machine learning skills in a collaborative, public setting.
The document discusses the process of selecting the best machine learning model, including evaluating multiple models on a holdout dataset to determine the best performing one. It notes common model types like logistic regression, decision trees, and neural networks that could be considered. It also addresses the need to split data into training, validation, and test sets to accurately assess model performance and avoid overfitting conclusions from multiple comparisons of models during selection.
3rd issue of Volume 8. A magazine in urdu language mainly based on spiritual treatment and learning. Many topics on ISLAM, SUFISM, SOCIAL PROBLEMS, SELF HELP, PSYCHOLOGY, HEALTH, SPIRITUAL TREATMENT etc. A Very useful magazine for everyone.
Zs 0992 teks viler dolina vukova (scanturion & zikateror & emeri)(5...zoran radovic
油
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to boost self-esteem and can serve as a healthy way to manage stress.
The document discusses the history and development of chocolate over centuries. It details how cocoa beans were first used by Mesoamerican cultures before being introduced to Europe. Chocolate then evolved from a luxury good to a mass-produced confection as production methods advanced and it became commercially available on a larger scale.
Zs 0995 zagor - zakon predaka (scanturion & enwil & quaresma & ...zoran radovic
油
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to boost self-esteem and can serve as a healthy way to manage stress.
This document contains summaries from multiple sessions of a machine learning zoomcamp. It introduces machine learning concepts like supervised learning, the CRISP-DM process, model selection, linear algebra, and the Python libraries NumPy and Pandas. It also discusses setting up an environment for machine learning and provides example data and models for tasks like email spam detection and car price prediction.
The document discusses the benefits of exercise for both physical and mental health. Regular exercise can improve cardiovascular health, reduce stress and anxiety, boost mood, and reduce the risk of diseases. The effects of exercise are wide-ranging and even a modest routine can lead to significant health improvements.
Docfoc.com dok holidej 003 - frenk larami - pakleni poker (matorimikica &...zoran radovic
油
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to increase gray matter volume in the brain and reduce risks for conditions like Alzheimer's and dementia.
The document discusses the benefits of exercise for mental health. It notes that regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise has also been shown to enhance self-esteem and quality of life.
This document summarizes a presentation about data science at OLX. It discusses OLX's moderation and recommender systems. For moderation, it describes OLX's machine learning models that automatically moderate listings for issues like duplicates, spam, and illegal/NSFW content. Moderators review flagged content. For recommendations, it discusses collaborative filtering and item embeddings to suggest relevant listings to users. It also outlines OLX's team structure, goal setting process, and expectations for data scientists, which include a focus on modeling, evaluation and some production work.
Whylogs is an open source tool for data monitoring that automatically creates statistical summaries called profiles of datasets. It helps with data monitoring by generating these profiles which can be compared over time to detect changes visually or programmatically. This allows issues like schema changes or bugs in data pipelines to be identified. The profiles have properties like being descriptive, lightweight and mergeable, which enables monitoring across distributed systems by allowing profile data to be logically merged. Whylogs thus provides a step towards observability of data systems.
The document outlines the plan and syllabus for a Data Engineering Zoomcamp hosted by DataTalks.Club. It introduces the four instructors for the course - Ankush Khanna, Sejal Vaidya, Victoria Perez Mola, and Alexey Grigorev. The 10-week course will cover topics like data ingestion, data warehousing with BigQuery, analytics engineering with dbt, batch processing with Spark, streaming with Kafka, and a culminating 3-week student project. Pre-requisites include experience with Python, SQL, and the command line. Course materials will be pre-recorded videos and there will be weekly live office hours for support. Students can earn a certificate and compete on a
This document discusses Zalando's use of AI to improve size and fit recommendations for customers. It outlines several challenges including varying size conventions, limited fit data for new items, and sparse customer purchase histories. It then describes Zalando's approaches to address these, including algorithms that use item images to predict sizes for new items lacking data (SizeNet) and models that learn from customers' past purchases and feedback to provide personalized size recommendations. The goal is to help customers find the right fit on their first purchase to reduce returns and improve the shopping experience.
AI-Powered Computer Vision Applications in Media Industry - Yulia PavlovaAlexey Grigorev
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Computer vision techniques like facial recognition and image captioning can help automate metadata generation for media companies. Facial recognition can identify people in photos to assist editors and improve searchability, while image captioning can propose captions. A case study of applying these techniques to photos from English Premier League football games achieved 99% accuracy for facial recognition and precision of 78.7% for image captioning. Combining the two allows generating customized captions that include names identified through facial recognition. Challenges remain when the automatic caption does not match details in the image.
This document discusses several paradoxes that can arise in data science. It begins by discussing modelling and simulations that can be used when data is unavailable. It then outlines Simpson's Paradox, where a trend seen in groups disappears or reverses when the groups are combined. Next, it discusses the accuracy paradox, where a metric stops being useful once it becomes the target. It also discusses the learnability-Godel paradox related to the limitations of mathematics according to Godel's incompleteness theorems. Finally, it discusses the law of unintended consequences as it relates to data science.
An algorithm is considered fair if its results and performance are independent of sensitive variables like gender, ethnicity, etc. Fairness can be introduced at different stages of model development, such as in data collection, preparation, and model selection. Techniques for identifying and mitigating bias include causal reasoning, explainability, fairness metrics, and counterfactuals. Counterfactual fairness evaluates predictions across different protected attribute values while holding other variables constant. Explainability helps ensure models make decisions for the right reasons. Overall fairness aims to achieve equal outcomes or opportunities across groups.
This document discusses MLOps at OLX, including:
- The main areas of data science work at OLX like search, recommendations, fraud detection, and content moderation.
- How OLX uses teams structured by both feature areas and roles to collaborate on projects.
- A maturity model for MLOps with levels from no MLOps to fully automated processes.
- How OLX has improved from siloed work to cross-functional teams and adding more automation to model creation, release, and application integration over time.
Introduction to Transformers for NLP - Olga PetrovaAlexey Grigorev
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Olga Petrova gives an introduction to transformers for natural language processing (NLP). She begins with an overview of representing words using tokenization, word embeddings, and one-hot encodings. Recurrent neural networks (RNNs) are discussed as they are important for modeling sequential data like text, but they struggle with long-term dependencies. Attention mechanisms were developed to address this by allowing the model to focus on relevant parts of the input. Transformers use self-attention and have achieved state-of-the-art results in many NLP tasks. Bidirectional Encoder Representations from Transformers (BERT) provides contextualized word embeddings trained on large corpora.
This document discusses the use of machine learning in online marketplaces. It outlines how machine learning is used for recommendations, search, trust and safety, seller experience, and pricing/monetization. Specific applications mentioned include collaborative and content-based recommendation systems, ranking models for search, automated content moderation, image quality assessment, dynamic pricing, and promoting listings. The document provides examples of algorithms like counting, collaborative filtering, learning to rank, and neural networks that power these machine learning applications in online marketplaces.
The document discusses the CRISP-DM methodology for machine learning projects. It describes the six main steps: 1) business understanding to define goals, 2) data understanding to analyze sources, 3) data preparation to transform data, 4) modeling to select the best model, 5) evaluation to validate goals are met, and 6) deployment to production. These steps provide an iterative process from problem definition to model deployment.
The document compares rule-based systems and machine learning for spam detection. It begins by showing examples of spam emails and rules to identify them. However, more rules are needed as spammers adapt, making rule-based systems complex. The document then introduces machine learning, which involves extracting features from email data, training a model on many examples, and using the model to classify new emails. This approach can learn from data automatically and perform better than hand-crafted rules.
ML Zoomcamp 1.1 - Introduction to Machine LearningAlexey Grigorev
油
This document introduces machine learning and how it can be used to predict car prices based on characteristics like year, make, mileage, and other available data. It explains that an expert can use this data to determine a car's price, and a machine learning model can be trained to do the same by learning patterns in the data. The model would be trained on sample data that contains the features known about each car along with the target price value. It could then be used to predict prices for new cars by taking in their features. This allows applying the patterns learned during training to make useful predictions without needing expert knowledge.
The document discusses machine learning use cases in online marketplaces. It outlines how ML can be used for search, recommendations, trust and safety, seller experience, and pricing/monetization. Specific applications include recommending similar products, learning user preferences for search rankings, detecting illegal/unsafe content, assessing listing quality, and determining optimal pricing. The document provides examples of algorithms like collaborative filtering, neural networks, and learning to rank that power these ML systems in marketplaces.
From Software Engineering To Machine LearningAlexey Grigorev
油
This document provides guidance on transitioning from a software engineering background to machine learning. It recommends learning fundamentals like Python, NumPy, and Pandas first before more complex algorithms. The best way to learn is through hands-on projects, starting with simple algorithms and evaluating models. Deploying models is described as easy for engineers but difficult for data scientists. Community involvement is encouraged to avoid working alone. Real-world projects are presented from domains like car pricing, customer churn, credit risk, and image classification to illustrate learning concepts.
3 hacks to accelerate your data science career Alexey Grigorev
油
This document provides 3 hacks to accelerate a data science career:
1. Be friends with your product manager to learn about prioritization, communication, planning, users, and marketing.
2. Be visible by giving demos of your work, creating frontends for models, speaking at internal events, and writing blog posts.
3. Become part of the data science community by participating in meetups and conferences.
Unit 1 Computer Hardware for Educational Computing.pptxRomaSmart1
油
Computers have revolutionized various sectors, including education, by enhancing learning experiences and making information more accessible. This presentation, "Computer Hardware for Educational Computing," introduces the fundamental aspects of computers, including their definition, characteristics, classification, and significance in the educational domain. Understanding these concepts helps educators and students leverage technology for more effective learning.
How to Unblock Payment in Odoo 18 AccountingCeline George
油
In this slide, we will explore the process of unblocking payments in the Odoo 18 Accounting module. Payment blocks may occur due to various reasons, such as exceeding credit limits or pending approvals. We'll walk through the steps to remove these blocks and ensure smooth payment processing.
APM event hosted by the South Wales and West of England Network (SWWE Network)
Speaker: Aalok Sonawala
The SWWE Regional Network were very pleased to welcome Aalok Sonawala, Head of PMO, National Programmes, Rider Levett Bucknall on 26 February, to BAWA for our first face to face event of 2025. Aalok is a member of APMs Thames Valley Regional Network and also speaks to members of APMs PMO Interest Network, which aims to facilitate collaboration and learning, offer unbiased advice and guidance.
Tonight, Aalok planned to discuss the importance of a PMO within project-based organisations, the different types of PMO and their key elements, PMO governance and centres of excellence.
PMOs within an organisation can be centralised, hub and spoke with a central PMO with satellite PMOs globally, or embedded within projects. The appropriate structure will be determined by the specific business needs of the organisation. The PMO sits above PM delivery and the supply chain delivery teams.
For further information about the event please click here.
ITI Turner Question Paper MCQ E-Book Free DownloadSONU HEETSON
油
ITI Turner Question Paper MCQ Book PDF Free Download. All Questions collected from NIMI Mock Test, CTS Bharat Skills Question Bank, Previous Exam papers. Helpful for CTS Trade Theory 1st & 2nd Year CBT Exam,油Apprentice test, AITT, ISRO, DRDO, NAVY, ARMY, Naval Dockyard, Tradesman, Training Officer, Instructor, RRB ALP CBT 2,油Railway Technician, CEPTAM, BRO, PWD, PHED, Air India, BHEL, BARC, IPSC, CISF, CTI, HSFC, GSRTC, GAIL, PSC, Viva, Tests, Quiz油& all other technical competitive exams.
This course provides students with a comprehensive understanding of strategic management principles, frameworks, and applications in business. It explores strategic planning, environmental analysis, corporate governance, business ethics, and sustainability. The course integrates Sustainable Development Goals (SDGs) to enhance global and ethical perspectives in decision-making.
How to Configure Proforma Invoice in Odoo 18 SalesCeline George
油
In this slide, well discuss on how to configure proforma invoice in Odoo 18 Sales module. A proforma invoice is a preliminary invoice that serves as a commercial document issued by a seller to a buyer.
Managing expiration dates of products in odooCeline George
油
Odoo allows users to set expiration dates at both the product and batch levels, providing flexibility and accuracy. By using Odoo's expiration date management, companies can minimize waste, optimize stock rotation, and maintain high standards of product quality. The system allows users to set expiration dates at both the product and batch levels, providing flexibility and accuracy.
How to Setup WhatsApp in Odoo 17 - Odoo 際際滷sCeline George
油
Integrate WhatsApp into Odoo using the WhatsApp Business API or third-party modules to enhance communication. This integration enables automated messaging and customer interaction management within Odoo 17.