Data Science Dojo

JUNE 1, 2023

Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

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Machine Learning Mastery

DECEMBER 31, 2022

Last Updated on January 1, 2023 While a logistic regression classifier is used for binary class classification, softmax classifier is a supervised learning algorithm which is mostly used when multiple classes are involved. Softmax classifier works by assigning a probability distribution to each class.

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Dataconomy

APRIL 18, 2023

Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures. AI systems use a combination of algorithms, machine learning techniques, and data analytics to simulate human intelligence. What is artificial intelligence?

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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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ODSC - Open Data Science

JULY 26, 2023

Machine learning is a subfield of artificial intelligence (AI) that enables computers to learn and make decisions or predictions without explicit programming. It involves feeding data to algorithms, which then generalize patterns and make inferences about unseen data. Common supervised learning tasks include classification (e.g.,

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Dataconomy

MAY 29, 2023

These algorithms allow AI systems to recognize patterns, forecast outcomes, and adjust to new situations. The applications of AI span diverse domains, including natural language processing, computer vision, robotics, expert systems, and machine learning. QR codes also contribute to access control and security within AI and ML systems.

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Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. Whereas in machine learning, the algorithm understands the data and creates the logic. Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning.

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Dataconomy

MAY 4, 2023

From predicting disease outbreaks to identifying complex medical patterns and helping researchers develop targeted therapies, the potential applications of machine learning in healthcare are vast and varied. What is machine learning? From personalized medicine to disease prevention, the possibilities are endless.

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How to Learn Machine Learning

MAY 14, 2023

Building a Solid Foundation in Mathematics and Programming To become a successful machine learning engineer, it’s essential to have a strong foundation in mathematics and programming. Mathematics is crucial because machine learning algorithms are built on concepts such as linear algebra, calculus, probability, and statistics.

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Dataconomy

OCTOBER 5, 2023

AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand. Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. Another form of machine learning algorithm is known as unsupervised learning.

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Pickl AI

AUGUST 1, 2023

In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types. What is Machine Learning? Supervised Learning Models Supervised learning involves training a model on labelled data, where the input features and corresponding target outputs are provided.

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Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

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Dataconomy

MARCH 3, 2023

As machine learning algorithms continue to evolve, financial institutions will be able to develop even more accurate and sophisticated asset pricing models, giving them a competitive edge in the market. As a result, financial analysts have turned to machine learning as a promising tool for improving asset pricing models.

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PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision. Also, you might want to check out our computer vision for deep learning program before you go.

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Data Science Dojo

SEPTEMBER 11, 2023

These complex algorithms are the backbone upon which our modern technological advancements rest and which are doing wonders for natural language communication. PaLM 2 stands for “ Progressive and Adaptive Language Model 2 ” and Llama 2 is short for “ Language Learning and Mastery Algorithm 2 ”.

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Mlearning.ai

JUNE 27, 2023

These variances provide a significant level of uncertainty and ambiguity, necessitating the use of computer vision algorithms to effectively and reliably process and understand this large array of data. The sheer volume of data necessary to train deep learning models exacerbates the problem.

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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. Differentiate between supervised and unsupervised learning algorithms.

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ODSC - Open Data Science

MARCH 22, 2023

Cleanlab is an open-source software library that helps make this process more efficient (via novel algorithms that automatically detect certain issues in data) and systematic (with better coverage to detect different types of issues). Data-centric AI instead asks how we can systematically engineer better data through algorithms/automation.

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ODSC - Open Data Science

FEBRUARY 10, 2023

The team found the new algorithm excelled by organizing the data from telescopes into categories. To do this, they first tested the range of algorithms to determine both precision and how often they provided false positives. Researchers analyzed over 150 terabytes of data which represented the observations of 820 nearby stars.

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Becoming Human

AUGUST 15, 2023

Introduction In the world of data science and machine learning, logistic regression is a powerful and widely-used algorithm. Logistic regression is a type of supervised learning algorithm. Conclusion In summary, logistic regression is a simple but effective algorithm for binary classification problems.

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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. Key concepts of AI The following are some of the key concepts of AI: Data:  AI requires vast amounts of data to learn and improve its performance over time.

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Heartbeat

OCTOBER 25, 2023

Bioinformatics algorithms and tools have played a crucial role in analyzing NGS data, enabling researchers to study genetic variations, gene expression patterns, and epigenetic modifications on a large scale. While bioinformatics has made remarkable strides in advancing biological research, it faces several challenges that must be overcome.

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IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

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IBM Journey to AI blog

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. Finally, we will look at some of the recent semi-supervised medical image segmentation algorithms.

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. What is machine learning (ML)?

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? This makes learning very slow or stops it altogether. said Ivern Ball.

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Dataconomy

MARCH 14, 2023

One major issue with conventional supervised learning approaches is that they lack scalability. On the other hand, self-supervised learning can utilize audio-only data, which is more readily available across a wide range of languages. This necessitates a flexible, efficient, and generalizable learning algorithm.

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Heartbeat

SEPTEMBER 20, 2023

This technology has broad applications, including aiding individuals with visual impairments, improving image search algorithms, and integrating optical recognition with advanced language generation to enhance human-machine interactions. Various algorithms are employed in image captioning, including: 1.

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Pickl AI

AUGUST 1, 2023

Text Vectorization Techniques Text vectorization is a crucial step in text mining, where text data is transformed into numerical representations that can be processed by Machine Learning algorithms. Sentiment analysis techniques range from rule-based approaches to more advanced machine learning algorithms.

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Google Research AI blog

APRIL 30, 2023

Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels.

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IBM Journey to AI blog

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. We stand on the frontier of an AI revolution. But we’ve faced a paradoxical challenge: automation is labor intensive. But this is starting to change.

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phData

AUGUST 24, 2023

Greater Accuracy Machine learning models can handle high-dimensional, nonlinear, and interactive relationships between variables. These nuanced algorithms can lead to more accurate and reliable credit scores and decisions. The model learns from these labels to predict the outcome of new, unseen data. loan default or not).

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 56

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Google Research AI blog

MARCH 28, 2023

Posted by Harsh Mehta, Software Engineer, and Walid Krichene, Research Scientist, Google Research Large deep learning models are becoming the workhorse of a variety of critical machine learning (ML) tasks. The most popular method for DP training in deep learning is differentially private stochastic gradient descent (DP-SGD).

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. What is machine learning (ML)?

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Heartbeat

FEBRUARY 15, 2023

It is a supervised learning methodology that predicts if a piece of text belongs to one category or the other. As a machine learning engineer, you start with a labeled data set that has vast amounts of text that have already been categorized. We pay our contributors, and we don’t sell ads.

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