ODSC - Open Data Science

JULY 26, 2023

As a senior data scientist, I often encounter aspiring data scientists eager to learn about machine learning (ML). In this comprehensive guide, I will demystify machine learning, breaking it down into digestible concepts for beginners. Common supervised learning tasks include classification (e.g.,

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Pickl AI

OCTOBER 9, 2023

This technology allows computers to learn from historical data, identify patterns, and make data-driven decisions without explicit programming. Unsupervised learning algorithms Unsupervised learning algorithms are a vital part of Machine Learning, used to uncover patterns and insights from unlabeled data.

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Data Science 101

OCTOBER 31, 2019

The former is a term used for models where the data has been labeled, whereas, unsupervised learning, on the other hand, refers to unlabeled data. Classification is a form of supervised learning technique where a known structure is generalized for distinguishing instances in new data. Clustering.

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Pickl AI

FEBRUARY 2, 2025

Classification: How it Differs from Association Rules Classification is a supervised learning technique that aims to predict a target or class label based on input features. These tools enable data scientists and analysts to build models efficiently, handle large datasets, and derive meaningful insights through association rules.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Large language models (LLMs) are a class of foundational models (FM) that consist of layers of neural networks that have been trained on these massive amounts of unlabeled data. Using a full-stack approach for deploying applications to the edge, a data scientist can perform fine-tuning, testing and deployment of the models.

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Pickl AI

DECEMBER 4, 2024

Summary: Data Science appears challenging due to its complexity, encompassing statistics, programming, and domain knowledge. However, aspiring data scientists can overcome obstacles through continuous learning, hands-on practice, and mentorship. However, many aspiring professionals wonder: Is Data Science hard?

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IBM Journey to AI blog

JULY 6, 2023

Alternatively, they might use labels, such as “pizza,” “burger” or “taco” to streamline the learning process through supervised learning. It can ingest unstructured data in its raw form (e.g., It can ingest unstructured data in its raw form (e.g.,

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Pickl AI

JULY 12, 2024

Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data. There are three main types of Machine Learning: supervised learning, unsupervised learning, and reinforcement learning.

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Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

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AWS Machine Learning Blog

OCTOBER 30, 2024

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval.

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Pickl AI

NOVEMBER 18, 2024

The main types are supervised, unsupervised, and reinforcement learning, each with its techniques and applications. Supervised Learning In Supervised Learning , the algorithm learns from labelled data, where the input data is paired with the correct output. predicting house prices).

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Heartbeat

OCTOBER 25, 2023

Empowering Data Scientists and Machine Learning Engineers in Advancing Biological Research Image from European Bioinformatics Institute Introduction: In biological research, the fusion of biology, computer science, and statistics has given birth to an exciting field called bioinformatics.

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Pickl AI

DECEMBER 3, 2024

The UCI Machine Learning Repository is a well-known online resource that houses vast Machine Learning (ML) research and applications datasets. It is a central hub for researchers, data scientists, and Machine Learning practitioners to access real-world data crucial for building, testing, and refining Machine Learning models.

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Pickl AI

NOVEMBER 28, 2024

These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Supervised Learning Supervised learning is one of the most common types of Machine Learning, where the algorithm is trained using labelled data.

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AWS Machine Learning Blog

MAY 30, 2023

Amazon SageMaker provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

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Pickl AI

FEBRUARY 12, 2024

Data Science interviews are pivotal moments in the career trajectory of any aspiring data scientist. Having the knowledge about the data science interview questions will help you crack the interview. Differentiate between supervised and unsupervised learning algorithms.

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Snorkel AI

APRIL 18, 2023

Typically, you let the experts read some articles, label them, and then use them as training data and train the supervised learning model. In fact, we burned our fingers in a previous project where we relied on domain scientists to label them all. To address all these problems, we looked into weak supervised learning.

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Snorkel AI

APRIL 18, 2023

Typically, you let the experts read some articles, label them, and then use them as training data and train the supervised learning model. In fact, we burned our fingers in a previous project where we relied on domain scientists to label them all. To address all these problems, we looked into weak supervised learning.

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Becoming Human

MAY 15, 2023

Note : Now, Start joining Data Science communities on social media platforms. These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey.

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Pickl AI

AUGUST 1, 2023

It helps in discovering hidden patterns and organizing text data into meaningful clusters. Topic Modeling and Document Clustering: Build a text mining project that performs topic modeling and document clustering. Cluster similar documents based on their content and explore relationships between topics.

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Pickl AI

SEPTEMBER 12, 2024

Data Science is the art and science of extracting valuable information from data. It encompasses data collection, cleaning, analysis, and interpretation to uncover patterns, trends, and insights that can drive decision-making and innovation.

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Pickl AI

AUGUST 9, 2024

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

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Pickl AI

OCTOBER 20, 2024

AI-related roles, such as Machine Learning Engineers, Data Scientists, and AI Developers, are in high demand. ML is a specific approach within AI that uses algorithms to identify patterns in data. Deep Learning is a subset of ML. It involves using neural networks with multiple layers to handle more complex data.

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Women in Big Data

DECEMBER 13, 2023

Benefits of NLP ? NLP has many applications – Machine Translation, Text Summarization, Searching, Question Answering, Named-Entity Recognition, Parts-of-Speech: (POS), Clustering, Sentiment Analysis, Text Classification, Chatbots and Virtual Assistants. A language model is a probability distribution over sequences of words.

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PyImageSearch

MARCH 30, 2023

Machine learning encompasses several strategies that teach algorithms to recognize patterns in data, guiding informed actions in similar settings. These strategies include: Supervised Learning: In this approach, data scientists provide ML systems with training data sets containing inputs and corresponding desired outputs.

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Snorkel AI

AUGUST 15, 2024

Data scientists train embedding models on unstructured text through a process called “self-supervised learning.” This process clusters words that often appear together closely in the model’s high-dimensional space. Nor do they understand the word “token” nor the lyrics to “The Lion Sleeps Tonight” by The Tokens.

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Snorkel AI

AUGUST 15, 2024

Data scientists train embedding models on unstructured text through a process called “self-supervised learning.” This process clusters words that often appear together closely in the model’s high-dimensional space. Nor do they understand the word “token” nor the lyrics to “The Lion Sleeps Tonight” by The Tokens.

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Snorkel AI

OCTOBER 6, 2023

Pre-training with unstructured data Pre-training with unstructured data sounds simple: gather proprietary data from across your organization and dump it all into a self-supervised learning pipeline. Data scientists can clean this up ahead of pre-training in a number of ways.

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Snorkel AI

SEPTEMBER 29, 2023

Visual object detection: A computer vision model may learn from captions or labels attached to pictures to predict whether photos contain things like dogs, cats, bridges, automobiles, or bicycles. Focusing primarily on developing data sets falls into the category of data-centric AI — which stands in contrast to model-centric AI.

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Pickl AI

SEPTEMBER 18, 2024

Their work environments are typically collaborative, involving teamwork with Data Scientists, software engineers, and product managers. Tools like pandas and SQL help manipulate and query data , while libraries such as matplotlib and Seaborn are used for data visualisation. accuracy, precision, recall, F1-score).

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Explosion

AUGUST 3, 2017

Prodigy solves this problem by letting data scientists conduct their own annotations, for rapid prototyping. You’ll collect more user actions, giving you lots of smaller pieces to learn from, and a much tighter feedback loop between the human and the model. Solutions to these problems could surely be developed – but… why?

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Snorkel AI

OCTOBER 6, 2023

Pre-training with unstructured data Pre-training with unstructured data sounds simple: gather proprietary data from across your organization and dump it all into a self-supervised learning pipeline. Data scientists can clean this up ahead of pre-training in a number of ways.

Data Scientist 52

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Snorkel AI

OCTOBER 6, 2023

Pre-training with unstructured data Pre-training with unstructured data sounds simple: gather proprietary data from across your organization and dump it all into a self-supervised learning pipeline. Data scientists can clean this up ahead of pre-training in a number of ways.

Data Science 59

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Pickl AI

DECEMBER 9, 2024

Summary: Inductive bias in Machine Learning refers to the assumptions guiding models in generalising from limited data. By managing inductive bias effectively, data scientists can improve predictions, ensuring models are robust and well-suited for real-world applications.

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Pickl AI

APRIL 26, 2024

Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Explain the difference between supervised and unsupervised learning. Data Analytics Certification Course by Pickl.AI What approach would you take?

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Pickl AI

SEPTEMBER 23, 2024

Hypothesis testing and regression analysis are crucial for making predictions and understanding data relationships. Machine Learning Supervised Learning includes algorithms like linear regression, decision trees, and support vector machines.

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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