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Avis et commentaires pour d'étudiants pour Tesla Stock Price Prediction using Facebook Prophet par Coursera Project Network

4.5
étoiles
45 évaluations
12 avis

À propos du cours

In this 1.5-hour long project-based course, you will learn how to build a Facebook Prophet Machine learning model in order to forecast the price of Tesla 30 days into the future. We will also visualize the historical performance of Tesla through graphs and charts using Plotly express and evaluate the performance of the model against real data using Google Finance in Google Sheets. We will also dive into a brief stock analysis of Tesla and we will discuss PE ratio, EPS, Beta, Market cap, Volume and price range of Tesla. We will end the project by automating the forecasting process in such a way that you will get the forecast of any of your favourite stock with all necessary visualization within a few seconds of uploading the data. By the end of this project, you will be confident in analyzing, visualizing and forecasting the price of any stock of your choice. Disclaimer: This project is intended for educational purpose only and is by no means a piece of Financial advice. Please consult your financial advisor before investing in stocks. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Meilleurs avis

AJ

7 avr. 2022

Nice Couse thanks Abhishek. I was able to understand the Prophet lib and with that I was able to make the predictions for bitcoin as well - https://www.prediction1.com/prediction/BTC

MS

6 févr. 2022

I really enjoyed this project. Beginner-friendly, clearly explained, and concise intro to FB Prophet. Thanks!

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1 - 15 sur 15 Avis pour Tesla Stock Price Prediction using Facebook Prophet

par natalie G

13 juin 2021

Fellow New Zealander in the USA here. I love your instructing, teaching and this concept so much! As a Technological Entrepreneur female Nerd, I am looking for more from you and will definitely use this on my stocks over and over again. By fire and By force I have installed this into my brain. I am bouncing and defeating all my competitors! Computer, AI and Data science rocks!!!!!

par Sahil S

29 déc. 2021

This is a great project that focuses on using machine learning to forecast stock prices using real-world examples and financial terminology. I highly recommend it to anyone who wants to start stock trading!

par Avinash J

7 avr. 2022

Nice Couse thanks Abhishek. I was able to understand the Prophet lib and with that I was able to make the predictions for bitcoin as well - https://www.prediction1.com/prediction/BTC

par Mohamed S

7 févr. 2022

I really enjoyed this project. Beginner-friendly, clearly explained, and concise intro to FB Prophet. Thanks!

par Keyur S

4 déc. 2021

This was a very well designed and guided project - would love doing something similar on AI and ML

par Dhruv T 4

29 juin 2022

Very good and easy project

par Dania D

28 juin 2022

great experience

par Horacio B R

28 juil. 2021

E​xcellent

par Joshua

8 juin 2021

Nil

par अच्छे व

6 mars 2022

It's a very good course for those who are just started in ML(Trading). It start's from basic and I think well mantain course to automate process in the end.

par Ajith B

16 juin 2021

A very good project indeed. I learnt Facebook Prophet and was an eye opener for me who doesn't know anything about stocks

par Vladyslav K

5 août 2021

Great hands on introduction to Prophet, would enjoy a deeper dive into other functions of this library next time

par Kleider S V G

4 mars 2022

Clear and concise!

par Jair C

28 sept. 2021

i​t´s so basic.

par Martín J M

2 janv. 2022

I​ts good if you have no idea about how to use python por: plotly, pandas, prophet etc. Maybe the pace and content are adequate for an hour class.

I​ would say its rather superficial. For instance, it teaches facebook prophet to predict if a Tesla stock increases or not in the near future. However, how is this any better than simple eye inference? Would have been better to showcase an example where it predicts an inflexion in the stock, not a monothonical extrapolation (which anyone could do by naked eye). Or talk briefly on how the prohpet fit works, its limitations, etc.