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DATA SCIENCE
DATA SCIENCE
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Machine Learning

Machine learning (ML) is a subset of artificial intelligence. It focuses on the study of computer algorithms that improve automatically on their own, through experience. These algorithms are used in a large variety of different applications, from computer vision to mathematical optimizations. ML algorithms are necessary when it is difficult or not feasible to develop conventional algorithms to perform a necessary task.

The four main types of ML include:

  • Supervised machine learning algorithms that can apply what has already been learned in previous situations to new data using labeled examples to predict possible future events.
  • Unsupervised machine learning algorithms are used when the information used to train the model is neither classified nor labeled. Unsupervised learning can infer a function to describe a hidden structure from unlabeled data. Likewise, the system isn’t intended to figure out the right output, but it explores the data and can draw inferences from datasets to describe hidden structures from unlabeled data.
  • Semi-supervised machine learning algorithms fall in between supervised and unsupervised learning. They use both labeled and unlabeled data for training, skewing towards unlabeled data. Semi- supervised learning is selected when the acquired labeled data requires qualified and appropriate resources to train/learn from that. Otherwise, unlabeled data acquisition typically needs no additional capital.
  • Reinforcement machine learning algorithms is a learning method that produces actions and discovers errors through its environment. This method allows the algorithm to automatically understand behavior within a specific context in order to maximize its performance. Reward feedback is needed for the agent to understand which action is best, and this is known as a reinforcement signal.
Machine Learning

Preparing ML Models

The way toward preparing a ML model includes giving a ML calculation (that is, the learning calculation) with preparing information to gain from. The...

by Data Science Team 1 year agoDecember 15, 2020
Machine Learning

Batch normalization in Neural Networks

Why can we use batch normalization? We normalize the input layer by adjusting and scaling the activations. For instance, once we have features from...

by Data Science Team 1 year agoDecember 18, 2020
Machine Learning

ImageNet Classification with Deep Convolutional Neural Networks

Theoretical  We prepared a huge, profound convolutional neural system to arrange the 1.3 million high-goals pictures in the LSVRC-2010 ImageNet preparing set into the...

by Data Science Team 1 year agoDecember 15, 2020
Machine Learning

Unsupervised Learning

When a model learns patterns and shares the information, it requires accurate data to help the machine learn those patterns. This is what machine...

by Data Science Team 1 year agoDecember 6, 2020
Machine Learning

K-fold Cross-Validation

Cross-validation is a statistical method used to estimate the skill of machine learning models. It is normally utilized in applied AI to analyze and...

by Data Science Team 1 year agoNovember 14, 2020
Machine Learning

Deep learning model by SHAP

Shapley Value Before introducing SHAP (SHapley Additive exPlanations), let take a glance on Shapley value which may be a solution concept in cooperative theory...

by Data Science Team 1 year agoNovember 5, 2020
Machine Learning

Introduction to Machine Learning for Beginners

We have seen Machine Learning as a buzzword for the past few years, the rationale for this could be the high amount of knowledge...

by Data Science Team 1 year agoDecember 17, 2020
Machine Learning

Everything You Need to Know About Artificial Neural Networks

  What are Artificial Neural Networks? A lot of the advances in AI are new statistical models, but the overwhelming majority of the advances...

by Data Science Team 1 year agoNovember 28, 2020
Machine Learning

Types of artificial neural networks

There are numerous kinds of artificial neural networks (ANN). Artificial neural networks are computational models that mimic natural neural arrangements and are utilized to...

by Data Science Team 1 year agoNovember 27, 2020
Machine Learning

What Do Data Scientists Do?

  In simple terms, a data scientist’s job is to research data for actionable insights. Specific tasks include: Identifying the data-analytics problems that provide...

by Data Science Team 1 year agoNovember 15, 2020
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