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29 Best Data Analytics Certification Online Courses & Tutorials

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Do you want to upgrade your skills with Best Data Analytics Certification Online to stand out in the industry? Here is a list of Best Data Analytics Courses Online, Training, Tutorials, and Classes to assist you to become a top Data Analyst. Now Big data, Data Science, Machine Learning, Deep Learning, Artificial Intelligence (AI), Analytics, Python, R, r-stats are the most trending and highly demanding subjects in every sector for almost every industry. Learn business analytics to get hands-on knowledge of big data analytics, data visualization, data management, and data mining as an analytics professional. The majority of the business professionals are upgrading their skills with Best Data Analytics Training to standout in their industry.


Writer identification for historical handwritten documents using a single feature extraction method

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The digitization of historical handwritten document images is important for the preservation of cultural heritage. Moreover, the transcription of text images obtained from digitization is necessary to provide efficient information access to the content of these documents. Handwritten Text Recognition (HTR) has become an important research topic in the areas of image and computational language ... [Show full abstract] processing that allows us to obtain transcriptions from text images. State-of-the-art HTR systems are, however, far from perfect. One difficulty is that they have to cope with image noise and handwriting variability.


Beginning Anomaly Detection Using Python Based Deep Learning PDF

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Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semi-supervised anomaly detection along with the basics of time series-based anomaly detection.


The most impressive Youtube Channels for you to Learn AI, Machine Learning, and Data Science.

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This channel publishes interviews with data scientists from big companies like Google, Uber, Airbnb, etc. From these videos, you can get an idea of what it is like to be a data scientist and acquire valuable advice to apply in your life. A new ML Youtube channel that everyone should check out, Machine Learning 101 posts explainer videos on beginner AI concepts. The channel also posts podcasts with expert data scientists and professionals working on AI in commercial industries. FreeCodeCamp is an incredible non-profit organization. It is an open-source community that offers a collection of resources that helps people learn to code for free and create their projects.


Automated Feature Engineering Using Neural Networks

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Data cleaning: Some people consider this feature engineering but it is really its own step. In short, you need to make sure the data is even useable before feature engineering is even possible. It involves fixing errors in the data, handling missing values, handling outliers, one-hot encoding, scaling features,and countless other things. In my opinion, data cleaning is the only step worse than feature engineering so anyone who finds a way to automate this step will be my new hero. Mean encoding: This step involves transforming categorical features like zip code into information useable by the model. For example, you might create a column that shows the average sales revenue for a zip code.


Use Machine Learning and GridDB to build a Production-Ready Stock Market Anomaly Detector

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In this project, we use GridDB to create a Machine Learning platform where we Kafka is used to import stock market data from Alphavantage, a market data provider. Tensorflow and Keras train a model that is then stored in GridDB, and then finally uses LSTM prediction to find anomalies in daily intraday trading history. The last piece is that the data is visualized in Grafana and then we configure GridDB to send notifications via its REST Trigger function to Twilio's Sendgrid. The actual machine learning portion of this project was inspired by posts on Towards Data Science and Curiously. This model and the data flow is also applicable to many other datasets such as predictive maintenance or machine failure prediction or wherever you want to find anomalies in time series data.


Something's Fishy -- New Funding To Tackle Illegal Activities At Sea Using Machine Learning And …

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Our objective is to develop an automated anomaly detection model based on recurrent neural networks—a machine learning technique commonly …


Supervised Learning with Azure

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Several steps need to be performed during the preparation phase to transform images/sounds into numerical vectors accepted by the algorithms. Regression on text data: Training data consists of texts whose numerical scores are already known. Several steps need to be performed during the preparation phase to transform the text into numerical vectors accepted by the algorithms. Examples: Housing prices, Customer churn, Customer Lifetime Value, Forecasting (time series), and Anomaly Detection.


Complete Machine Learning and Data Science: Zero to Mastery

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This is a brand new Machine Learning and Data Science course just launched January 2020 and updated this month with the latest trends and skills! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 270,000 engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, other top tech companies. Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries).


Statistics for Data Science and Business Analysis

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Free Coupon Discount - Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis Created by 365 Careers, 365 Careers Team Students also bought SQL - MySQL for Data Analytics and Business Intelligence The Complete SQL Bootcamp 2020: Go from Zero to Hero Microsoft Power BI - A Complete Introduction Deep Learning A-Z: Hands-On Artificial Neural Networks Data Science A-Z: Real-Life Data Science Exercises Included Preview this Udemy Course GET COUPON CODE Description Is statistics a driving force in the industry you want to enter? Do you want to work as a Marketing Analyst, a Business Intelligence Analyst, a Data Analyst, or a Data Scientist? Well then, you've come to the right place! Statistics for Data Science and Business Analysis is here for you with TEMPLATES in Excel included! This is where you start.