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Sales Prediction| Using Time Series| End-to-End Understanding| Part -2

Towards AI

Please refer to Part 1– to understand what is Sales Prediction/Forecasting, the Basic concepts of Time series modeling, and EDA I’m working on Part 3 where I will be implementing Deep Learning and Part 4 where I will be implementing a supervised ML model. This is part 2, and you will learn how to do sales prediction using Time Series.

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The AI Process

Towards AI

In general, the results of current journal articles on AI (even peer-reviewed) are irreproducible. Data preparation: This step includes the following tasks: data preprocessing, data cleaning, and exploratory data analysis (EDA). Training: This step includes building the model, which may include cross-validation.

AI 98
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Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit?—?Part 2 of 3

Mlearning.ai

This is part 2 of the three-series article. If you are here for the first time then please check out this article first. The scope of this article is quite big, we will exercise the core steps of data science, let's get started… Project Layout Here are the high-level steps for this project. dt.strftime('%Y%m').astype(int)

Python 52
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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. By understanding crucial concepts like Machine Learning, Data Mining, and Predictive Modelling, analysts can communicate effectively, collaborate with cross-functional teams, and make informed decisions that drive business success.

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Large Language Models: A Complete Guide

Heartbeat

A small portion of the LLM ecosystem; image from scalevp.com In this article, we will provide a comprehensive guide to training, deploying, and improving LLMs. In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning.