How to Learn Machine Learning

DECEMBER 15, 2024

Deep Learning Specialization Developed by deeplearning.ai Sale Why Machines Learn: The Elegant Math Behind Modern AI Hardcover Book Ananthaswamy, Anil (Author) English (Publication Language) 480 Pages - 07/16/2024 (Publication Date) - Dutton (Publisher) Buy on Amazon 3.

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PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

By following this data-driven approach, the classifier can accurately categorize new inputs based on their similarity to the learned characteristics of each class, capturing the nuances and diversity within each category. For the classfier, we employed a classic ML algorithm, k-NN, using the scikit-learn Python module.

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube Deploy LLMs in production Deploy Model Azure —  Use endpoints for inference — Azure Machine Learning | Microsoft Learn AWS + Huggingface —  Exporting ?

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Heartbeat

APRIL 17, 2023

In this article, we will discuss how to perform Named Entity Recognition with SpaCy , a popular Python library for NLP. NRE is a complex task that involves multiple steps and requires sophisticated machine learning algorithms like Hidden Markov Models (HMMs) , Conditional Random Fields (CRFs), and Support Vector Machines (SVMs) be present.

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Heartbeat

MAY 22, 2023

Data preprocessing The image frames are preprocessed by applying techniques like cropping, rotating, resizing, color correction, image smoothening and noise correction to improve the feature vector and the corresponding accuracy of the model. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Key programming languages include Python and R, while mathematical concepts like linear algebra and calculus are crucial for model optimisation. during the forecast period.

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IBM Journey to AI blog

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

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Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. Develop AI models using machine learning or deep learning algorithms. How to create an artificial intelligence?

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IBM Journey to AI blog

DECEMBER 19, 2023

Unsupervised learning Unsupervised learning techniques do not require labeled data and can handle more complex data sets. Unsupervised learning is powered by deep learning and neural networks or auto encoders that mimic the way biological neurons signal to each other.

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Pickl AI

SEPTEMBER 23, 2024

AI, particularly Machine Learning and Deep Learning uses these insights to develop intelligent models that can predict outcomes, automate processes, and adapt to new information. Deep Learning: Advanced neural networks drive Deep Learning , allowing AI to process vast amounts of data and recognise complex patterns.

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ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on.

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Heartbeat

MARCH 21, 2023

Keras is popular high-level API machine learning framework in python that was created by Google. Hinge Losses  — Another set of losses for classification problems, but commonly used in support vector machines. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Heartbeat

SEPTEMBER 28, 2023

Import Libraries First, import the required Python libraries, such as Comet ML, Optuna, and scikit-learn. Model Training We train multiple machine learning models, including Logistic Regression, Random Forest, Gradient Boosting, and Support Vector Machine. Step-by-step guide: How the project works. ?

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Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Examples include linear regression, logistic regression, and support vector machines.

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Pickl AI

SEPTEMBER 3, 2023

The following blog will provide you a thorough evaluation on how Anomaly Detection Machine Learning works, emphasising on its types and techniques. Further, it will provide a step-by-step guide on anomaly detection Machine Learning python. Key Takeaways: As of 2021, the market size of Machine Learning was USD 25.58

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IBM Journey to AI blog

AUGUST 28, 2023

Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification. posts, comments and product reviews) to understand how customers perceive their products or services.

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DagsHub

DECEMBER 23, 2024

Key Characteristics Static Dataset : Works with a predefined set of unlabeled examples Batch Selection : Can select multiple samples simultaneously for labeling because of which it is widely used by deep learning models. Pool-Based Active Learning Scenario : Classifying images of artwork styles for a digital archive.  

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Mlearning.ai

MAY 23, 2023

Another example can be the algorithm of a support vector machine. Hence, we have various classification algorithms in machine learning like logistic regression, support vector machine, decision trees, Naive Bayes classifier, etc. What is deep learning?

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Pickl AI

AUGUST 9, 2024

Apache Spark A fast, in-memory data processing engine that provides support for various programming languages, including Python, Java, and Scala. Students should learn about Spark’s core concepts, including RDDs (Resilient Distributed Datasets) and DataFrames. Students should learn about neural networks and their architecture.

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Mlearning.ai

MARCH 1, 2023

Implementation of loss functions for classification task in Python Here is the link to the Kaggle notebook code. Loss functions for binary classification: Hinge loss : It’s mainly developed to be used with Support Vector Machine (SVM) models in machine learning. What are the loss functions?

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phData

AUGUST 24, 2023

Various machine learning algorithms can be used for credit scoring and decisioning, including logistic regression, decision trees, random forests, support vector machines, and neural networks. Furthermore, Snowflake provides native support for machine learning algorithms and tools.

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DagsHub

APRIL 21, 2024

Moving the machine learning models to production is tough, especially the larger deep learning models as it involves a lot of processes starting from data ingestion to deployment and monitoring. It provides different features for building as well as deploying various deep learning-based solutions.

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Heartbeat

MARCH 8, 2023

Text categorization is supported by a number of programming languages, including R, Python, and Weka, but the main focus of this article will be text classification with R. The e1071 package provides a suite of statistical classification functions, including support vector machines (SVMs), which are commonly used for spam detection.

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Pickl AI

NOVEMBER 18, 2024

spam detection), you might choose algorithms like Logistic Regression , Decision Trees, or Support Vector Machines. For unSupervised Learning tasks (e.g., On the other hand, overfitting arises when a model is too complex, learning noise and irrelevant details rather than generalisable trends.

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Pickl AI

SEPTEMBER 12, 2024

Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.

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Mlearning.ai

JUNE 8, 2023

Sentence embeddings can also be used in text classification by representing entire sentences as high-dimensional vectors and then feeding them into a classifier. Doc2Vec SBERT InferSent Universal Sentence Encoder Top 4 Sentence Embedding Techniques using Python! There are several widely-used models listed below.

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