Remove Data Collection Remove Deep Learning Remove Predictive Modeling
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How to Build a Real Estate Price Prediction Model?

Analytics Vidhya

Introduction As a data scientist, you have the power to revolutionize the real estate industry by developing models that can accurately predict house prices. This blog post will teach you how to build a real estate price prediction model from start to finish. appeared first on Analytics Vidhya.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.

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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

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The quest for high-quality data

O'Reilly on Data

Even if we boosted the quality of the available data via unification and cleaning, it still might not be enough to power the even more complex analytics and predictions models (often built as a deep learning model). An important paradigm for solving both these problems is the concept of data programming.

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What is predictive analytics? Transforming data into future insights

CIO Business Intelligence

Benefits of predictive analytics Predictive analytics makes looking into the future more accurate and reliable than previous tools. Retailers often use predictive models to forecast inventory requirements, manage shipping schedules, and configure store layouts to maximize sales.

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15 best data science bootcamps for boosting your career

CIO Business Intelligence

It’s a fast growing and lucrative career path, with data scientists reporting an average salary of $122,550 per year , according to Glassdoor. Here are the top 15 data science boot camps to help you launch a career in data science, according to reviews and data collected from Switchup. Data Science Dojo.

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R vs Python: What’s the Best Language for Natural Language Processing?

Sisense

Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib. These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. Libraries used for NLP are: NLTK, gensim, SpaCy , glove, and Scikit-Learn.