Analytics Vidhya

SEPTEMBER 15, 2021

This article was published as a part of the Data Science Blogathon Introduction Data is present everywhere. Any action we perform generates some or the other form of data. But this data might not be present in a structured form. A beginner starting with the data field is often trained for datasets in standard formats like […]. The post How to Extract Tabular Data from Doc files Using Python?

Python 400

Python Data Science ETL 400

O'Reilly Media

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The results gave us insight into what our subscribers are paid, where they’re located, what industries they work for, what their concerns are, and what sorts of career development opportunities they’re pursuing. While it’s sadly premature to say that the survey took place at the end of the COVID-19 pandemic (though we can all hope), it took place at a time when restrictions were loose

AI 145

AI AI Machine Learning ML 145

Eugene Yan

SEPTEMBER 14, 2021

An overview of system design, candidate retrieval, and ranking, with industry examples.

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DeepMind

SEPTEMBER 16, 2021

We argue that merely using curiosity for fast environment exploration or as a bonus reward for a specific task does not harness the full potential of this technique and misses useful skills. Instead, we propose to shift the focus towards retaining the behaviours which emerge during curiosity-based learning. We posit that these self-discovered behaviours serve as valuable skills in an agent’s repertoire to solve related tasks.

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Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

Analytics Vidhya

SEPTEMBER 12, 2021

This article was published as a part of the Data Science Blogathon Map, Filter, and Reduce are paradigms of functional programming. What is functional programming? Functional programming, as the name suggests, computes through the evaluation of functions. They allow us to write simpler, shorter code with faster implementation methods. In functional programming, code relies entirely on […].

Data Science 398

Data Science Python 398

Dlabs.ai

SEPTEMBER 15, 2021

Every business wants to make a profit. And machine learning can help. Price prediction powered by machine learning is one of the most powerful tools in any company’s toolkit. Because automated price forecasting can help you stay in sync with your market and, ultimately, improve the effectiveness of your sales process. In this post, we’ll tell you everything you need to know about what price prediction is, how it works, and its potential benefits for your business.

Machine Learning 52

Machine Learning Automation ML Artificial Intelligence 52

DeepMind

SEPTEMBER 16, 2021

We argue that merely using curiosity for fast environment exploration or as a bonus reward for a specific task does not harness the full potential of this technique and misses useful skills. Instead, we propose to shift the focus towards retaining the behaviours which emerge during curiosity-based learning. We posit that these self-discovered behaviours serve as valuable skills in an agent’s repertoire to solve related tasks.

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Analytics Vidhya

SEPTEMBER 16, 2021

Objective Understand what is Cross-sell using Vehicle insurance data. Learn how to build a model for cross-sell prediction. Introduction If you are a Machine learning enthusiast or a data science beginner, it’s important to have a guided journey and also exposure to a good set of projects.In this article, We will walk through a beginner […].

Machine Learning 395

Machine Learning Python Data Science 395

Analytics Vidhya

SEPTEMBER 13, 2021

This article was published as a part of the Data Science Blogathon Spark is a cluster computing platform that allows us to distribute data and perform calculations on multiples nodes of a cluster. The distribution of data makes large dataset operations easier to process. Here each node is referred to as a separate machine working on […]. The post Beginner’s Guide To Create PySpark DataFrame appeared first on Analytics Vidhya.

Data Science 393

Data Science Python 393

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Generative AI

Analytics Vidhya

SEPTEMBER 14, 2021

This article was published as a part of the Data Science Blogathon Introduction Data Science is a team sport, we have members adding value across the analytics/data science lifecycle so that it can drive the transformation by solving challenging business problems. We have multiple team members in a data science team: data engineers who create the […].

Data Scientist 391

Data Scientist Data Science 391

Analytics Vidhya

SEPTEMBER 15, 2021

This article was published as a part of the Data Science Blogathon Introduction Boosting is an ensemble modelling technique that was first presented by Freund and Schapire in the year 1997, since then, Boosting has been a prevalent technique for tackling binary classification problems. These algorithms improve the prediction power by converting a number of weak […].

Algorithm 362

Algorithm Data Science Machine Learning 362

Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon In this article, we will be learning about how to apply k-fold cross-validation to a deep learning image classification model. Like my other articles, this article is going to have hands-on experience with code. This article will initially start with the theory part then […]. The post How to Apply K-Fold Averaging on Deep Learning Classifier appeared first on Analytics Vidhya.

Deep Learning 362

Deep Learning Data Science Python 362

Analytics Vidhya

SEPTEMBER 17, 2021

This article was published as a part of the Data Science Blogathon Introduction In the previous article, we have talked about BERT, Its Usage, And Understood some of its underlying Concepts. This article is intended to show how one can implement the learned concept to create a spam classifier using BERT. Table Of Contents Introduction Understanding […].

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BERT Python Data Science NLP 335

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

LLM

Analytics Vidhya

SEPTEMBER 13, 2021

This article was published as a part of the Data Science Blogathon Introduction Let’s look at a practical application of the supervised NLP fastText model for detecting sarcasm in news headlines. About 80% of all information is unstructured, and text is one of the most common types of unstructured data. Due to its chaotic nature, analyzing, […].

NLP 332

NLP Data Science Python Machine Learning 332

Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon Introduction More often than not, while performing an EDA, we are faced with a situation to display information with respect to geographical locations. For example, for a COVID 19 dataset, one may want to show the number of cases in various areas. Here is […]. The post How to Visualise data in Maps Using GeoPandas appeared first on Analytics Vidhya.

Data Science 326

Data Science Python 326

Analytics Vidhya

SEPTEMBER 11, 2021

This article was published as a part of the Data Science Blogathon Overview When Apache Cassandra first came out, it included a command-line interface for dealing with thrift. Manipulation of data in this manner was inconvenient and caused knowing the API’s intricacies. Although the Cassandra query language is like SQL, its data modeling approaches are entirely […].

Data Science 323

Data Science Python 323

Analytics Vidhya

SEPTEMBER 14, 2021

This article was published as a part of the Data Science Blogathon image source: Author The Importance of Data Visualization A huge amount of data is being generated every instant due to business activities in globalization. Companies are extracting useful information from such generated data to make important business decisions. Exploratory Data analysis can help […].

Data Analysis 315

Data Analysis Data Science Python 315

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Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon Introduction Unsupervised learning, where there are no predefined labels for the data and the model segments the data into groups by inferring patterns and extracting features from the data, is at the heart of the data science problems. In the machine learning world, Segmentation […].

Data Science 315

Data Science Machine Learning Deep Learning 315

Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss the mathematical intuition behind Naive Bayes Classifiers, and we’ll also see how to implement this on Python. This model is easy to build and is mostly used for large datasets. It is a probabilistic machine learning […]. The post Naive Bayes Algorithm: A Complete guide for Data Science Enthusiasts appeared first on Analytics Vidhya.

Data Science 315

Data Science Algorithm Machine Learning Python 315

Analytics Vidhya

SEPTEMBER 14, 2021

This article was published as a part of the Data Science Blogathon R programing language was developed for statistical computing and graphics which makes it one of the desired candidates for Data Science and Analysis. Even though it might not hold much popularity among the newcomers in the field, many veterans and seasoned data scientists favour […].

Data Scientist 304

Data Scientist Data Science Machine Learning 304

Analytics Vidhya

SEPTEMBER 14, 2021

This article was published as a part of the Data Science Blogathon Overview The hardest thing is to keep things simple and that’s true in data science as well. In any data science project, the iterative process of refining the data, fine-tuning the models, deploying them is a continuous process. With all the advancements in tools, […]. The post How To Evaluate The Business Value Of a Machine Learning Model appeared first on Analytics Vidhya.

Machine Learning 302

Machine Learning Data Science Python 302

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Analytics Vidhya

SEPTEMBER 15, 2021

This article was published as a part of the Data Science Blogathon Preparing documents is one of the most critical tasks that every responsible business analyst does. A Business Analyst not only documents the clients’ requirements but also happens to document the progress and every change that has occurred during the project lifecycle. It is vital […].

Data Science 296

Data Science 296

Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon Introduction Analyzing texts is far more complicated than analyzing typical tabulated data (e.g. retail data) because texts fall under unstructured data. Textual data, even though very important, vary considerably in lexical and morphological standpoints. Different people express themselves quite differently when it comes to […].

Natural Language Processing 293

Natural Language Processing Data Science NLP Python 293

Analytics Vidhya

SEPTEMBER 13, 2021

This article was published as a part of the Data Science Blogathon Dear readers, In this blog, we will learn what n-grams are and explore them on text data in Python. It’s completely alright even if you have never heard of the term “n-grams” before. We will study and implement n-grams right from scratch! The objective […]. The post What Are n-grams and How to Implement Them in Python?

Python 291

Python Data Science NLP Machine Learning 291

Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon PySpark Column Operations plays a key role in manipulating and displaying desired results of PySpark DataFrame. It is important to know these operations as one may always require any or all of these while performing any PySpark Exercise. PySpark DataFrame is built over Spark’s […].

Data Science 293

Data Science Python 293

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Data Analysis

Analytics Vidhya

SEPTEMBER 13, 2021

This article was published as a part of the Data Science Blogathon In simple terms, Computer vision means providing human-like vision to the computer. As human beings, it is very easy for us to recognize any object. We can easily recognize hills, trees, land, animals, etc. but computers do not have eyes nor brains, so it […]. The post Active Contours – A Method for Image Segmentation in Computer Vision appeared first on Analytics Vidhya.

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Computer Vision Data Science Python Machine Learning 284

Analytics Vidhya

SEPTEMBER 14, 2021

This article was published as a part of the Data Science Blogathon Introduction Deep learning has evolved a lot in recent years and we all are excited to build deeper architecture networks to gain more accuracies for our models. These techniques are widely tried for Image related works like classification, clustering, or synthesis. Going deep may […].

Deep Learning 283

Deep Learning Data Science Python 283

Analytics Vidhya

SEPTEMBER 13, 2021

This article was published as a part of the Data Science Blogathon Visualization plays an important role in gaining quality insights from the data. Our traditional data visualization techniques are already playing a significant role in obtaining insights. But it’s always useful to bring and adapt new visualization techniques to create more appealing plots.

Data Science 267

Data Science Python 267