Solved end-to-end Data Science Projects in Telecommunications

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Data Science Projects in Telecommunications

Build a Text Classification Model with Attention Mechanism NLP

In this NLP Project, you will learn to build a multi class text classification model with attention mechanism.

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Build a Multi ClassText Classification Model using Naive Bayes

Implement the Naive Bayes Algorithm to build a multi class text classification model in Python.

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Azure Deep Learning-Deploy RNN CNN models for TimeSeries

In this Azure MLOps Project, you will learn to perform docker-based deployment of RNN and CNN Models for Time Series Forecasting on Azure Cloud.

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Build Multi Class Text Classification Models with RNN and LSTM

In this Deep Learning Project, you will use the customer complaints data about consumer financial products to build multi-class text classification models using RNN and LSTM.

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Skip Gram Model Python Implementation for Word Embeddings

Skip-Gram Model word2vec Example -Learn how to implement the skip gram algorithm in NLP for word embeddings on a set of documents.

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Deep Learning Project for Time Series Forecasting in Python

Deep Learning for Time Series Forecasting in Python -A Hands-On Approach to Build Deep Learning Models (MLP, CNN, LSTM, and a Hybrid Model CNN-LSTM) on Time Series Data.

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GCP MLOps Project to Deploy ARIMA Model using uWSGI Flask

Build an end-to-end MLOps Pipeline to deploy a Time Series ARIMA Model on GCP using uWSGI and Flask

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Predict Churn for a Telecom company using Logistic Regression

Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.

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NLP Project for Multi Class Text Classification using BERT Model

In this NLP Project, you will learn how to build a multi-class text classification model using using the pre-trained BERT model.

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FEAST Feature Store Example for Scaling Machine Learning

FEAST Feature Store Example- Learn to use FEAST Feature Store to manage, store, and discover features for customer churn prediction machine learning project.

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Time Series Forecasting Project-Building ARIMA Model in Python

Build a time series ARIMA model in Python to forecast the use of arrival rate density to support staffing decisions at call centres.

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Time Series Project to Build a Multiple Linear Regression Model

Learn to build a Multiple linear regression model in Python on Time Series Data

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Build Time Series Models for Gaussian Processes in Python

Time Series Project - A hands-on approach to Gaussian Processes for Time Series Modelling in Python

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Build ARCH and GARCH Models in Time Series using Python

In this Project we will build an ARCH and a GARCH model using Python

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AWS MLOps Project to Deploy Multiple Linear Regression Model

Build and Deploy a Multiple Linear Regression Model in Python on AWS

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AWS MLOps Project for Gaussian Process Time Series Modeling

MLOps Project to Build and Deploy a Gaussian Process Time Series Model in Python on AWS

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AWS MLOps Project for ARCH and GARCH Time Series Models

Build and deploy ARCH and GARCH time series forecasting models in Python on AWS .

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Time Series Analysis with Facebook Prophet Python and Cesium

Time Series Analysis Project - Use the Facebook Prophet and Cesium Open Source Library for Time Series Forecasting in Python

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Churn Prediction in Telecom using Machine Learning in R

Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.

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Customer Love

I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop Admin, Hadoop projects. I have been happy with every project. They have really brought me into the forefront of Data Science and Big data. I would recommend this to everyone. It is more than worth the price. After working with them I feel so much more employable for current projects.

Ray han

Tech Leader | Stanford / Yale University

I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good theoretical knowledge, the practical approach, real word application, and deployment knowledge were missing. ProjectPro helped me bridge that gap. ProjectPro has real-time projects that helped me improve my skills. What I liked most is that I get exposure to so many projects, given the work nature I wouldn't have gotten exposure to such a variety of projects and their approaches. It is helping me apply knowledge to other projects too. I highly recommend ProjectPro to everyone who wants to excel in their DataScience career.

Ameeruddin Mohammed

ETL (Abintio) developer at IBM

ProjectPro is a unique platform and helps many people in the industry to solve real-life problems with a step-by-step walkthrough of projects. A platform with some fantastic resources to gain hands-on experience and prepare for job interviews. I would highly recommend this platform to anyone looking to upskill and stay updated with the latest projects and solutions. Overall this platform is awesome and worth the money spent as we get a lot of value out of it and helps soar our career to greater heights.

Anand Kumpatla

Sr Data Scientist @ Doubleslash Software Solutions Pvt Ltd

As a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. Very few ways to do it are Google, YouTube, etc. I was one of them too, and that's when I came across ProjectPro while watching one of the SQL videos on the E-Learning Bridge YouTube channel. One of the standout features was that it featured real projects on topics I just read about, across different job descriptions at the time. The main issue was the right path to guide us in using these tools and adding to the resume, and that's exactly what ProjectPro got me through. The fact that I can have a reliable route and videos explaining each tool in detail really motivated me to continue with the platform. Another thing we all struggle with is how to really connect with someone if we're stuck somewhere because there are so many solutions. But this has also been solved by experts we can chat with and believe me when I say this they will do whatever it takes to solve your problem even if it takes longer than expected. In my sophomore year of college and getting hands-on exposure to technologies like PySpark, NLP, Kafka, etc, and being able to really apply the theory and work on a project from start to finish really boosted my confidence in general!

Savvy Sahai

Data Science Intern, Capgemini

I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills in Data Engineering/Science and hoping to find real-world projects fortunately, I came across Project Pro. Project Pro helped me by providing an in-depth explanation of the end-to-end real-world data engineering projects. From data extraction, transformation, and storage up to data visualization. I learned more about Kafka, AWS, NI-FI, and Spark. Thru the help of the knowledge I gained from Project Pro, I was able to do well in the coding exams, interview and helped me land a job at EY. I will recommend every aspiring data professional as well as existing data science/engineer expert to try Project Pro to enhance their knowledge.

Ed Godalle

Director Data Analytics at EY / EY Tech

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Jingwei Li

Graduate Research assistance at Stony Brook University

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Abhinav Agarwal

Graduate Student at Northwestern University

Having worked in the field of Data Science, I wanted to explore how I can implement projects in other domains, So I thought of connecting with ProjectPro. A project that helped me absorb this topic was "Credit Risk Modelling". To understand other domains, it is important to wear a thinking cap and that's where ProjectPro helped me. I also got a chance to talk to experts who have worked on these domains - they helped me by walking through the project. Kudos to the ProjectPro team!

Gautam Vermani

Data Consultant at Confidential