The Personal MS(DS) is an initiative to customize the Data Science Masters roadmap according to one's interests hence providing complete autonomy to the learner. The intuition behind #thepersonalmsds is to upgrade skills without formally enrolling into a Master's program at a University - EshbanTheLearner/thepersonalMSDS-v2

This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of Data Science. With every class, you will develop new skills and improve your understanding of this challenging yet lucrative field of Data Science. This course is fun and exciting, but at the same time, we dive deep into Machine Learning. Moreover, the course is packed with practical exercises that are based on real-life examples.

Build predictive deep learning models using Keras & Tensorflow Python, Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc. Create Neural network models in Python using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts. Instructor: Start Tech Academy Enroll Now - Neural Networks (ANN) using Keras and TensorFlow in Python About this Course You are looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in Python, right? You have found the right Neural Networks course! Add To Cart - GET COUPON CODE After completing this course you will be able to: Identify the business problem which can be solved using Neural network Models.

Caution: This timeline is tailored for @EshbanTheLearner and might not be suitable for everyone. Today's Progress: Today I continued with the Google Cloud Platform Big Data and Machine Learning Fundamentals course of Data Engineering with Google Cloud Professional Certificate on Coursera. Today's Progress: Today I enrolled in the Google Cloud Platform Big Data and Machine Learning Fundamentals course of Data Engineering with Google Cloud Professional Certificate on Coursera. Today's Progress: Today I ended and reviewd the Time Series Analysis in Python 2020 course on udemy. Today's Progress: Today I continued the Time Series Analysis in Python 2020 course on udemy.

Customer Analytics in Python 2020 Get udemy course coupon code Customer Analytics in Python – the place where marketing and data science meet! What will you learn in this course? We will introduce you to the relevant theory that you need to start performing customer analytics. Then we will perform cluster analysis and dimensionality reduction to help you segment your customers. What you'll learn Master beginner and advanced customer analytics Learn the most important type of analysis applied by mid and large companies Gain access to a professional team of trainers with exceptional quant skills Wow interviewers by acquiring a highly desired skill Understand the fundamental marketing modeling theory: segmentation, targeting, positioning, marketing mix, and price elasticity; Apply segmentation on your customers, starting from raw data and reaching final customer segments; Perform K-means clustering with a customer analytics focus; Apply Principal Components Analysis (PCA) on your data to preprocess your features; Combine PCA and K-means for even more professional customer segmentation; Deploy your models on a different dataset; Learn how to model purchase incidence through probability of purchase elasticity; Model brand choice by exploring own-price and cross-price elasticity; Complete the purchasing cycle by predicting purchase quantity elasticity Carry out a black box deep learning model with TensorFlow 2.0 to predict purchasing behavior with unparalleled accuracy Be able to optimize your neural networks to enhance results Description Data science and Marketing are two of the key driving forces that help companies create value and stay on top in today's fast-paced economy.

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