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Let’s dive into data science with python and predict stock prices and customer sentiment.
machine learning / ai ? How to learn machine learning in python? And what is transfer learning ? How to use it ? How to create a sentiment classification algorithm in python? How to train a neural network for stock price prediction?
Good questions here is a point to start searching for answers
In the world of today and especially tomorrow machine learning and artificial intelligence will be the driving force of the economy. Data science No matter who you are, an entrepreneur or an employee, and in which industry you are working in, machine learning (especially deep learning neural networks) will be on your agenda.
From my personal experience I can tell you that companies will actively searching for you if you aquire some skills in the data science field. Diving into this topic can not only immensly improve your career opportunities but also your job satisfaction!
It’s time to get your hands dirty and dive into one of the hottest topics on this planet.
To me the best way to get exposure is to do it Hands on . And that’s exactly what we do. Together we will go through the whole process of data import, preprocess the data , creating an long short term neural network in keras (LSTM), training the neural network and test it ( make predictions)
Specification: neural networks for sentiment and stock price prediction
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22 reviews for neural networks for sentiment and stock price prediction
Add a review
| Price | $17.99 |
|---|---|
| Provider | |
| Duration | 3 hours |
| Year | 2022 |
| Level | Beginner |
| Language | English ... |
| Certificate | Yes |
| Quizzes | No |
$17.99
Tom Kindred –
Very basic a lays out one solution vs discussing what approaches could be used and why this one was used vs the other approaches.
YA li –
internet connection is awful
Willie SS –
Learning steps by steps with better understanding on LSTM
Elisio –
Probably the best ML course for finance on Udemy I have done so far. Not only is Dan passionate which helps drive you, the course itself is in fact useful and focuses on a practical approach. The future X days prediction as well as the market sentiment puts this course above many other ML finance courses.
Amir Ghiasi –
Sessions 1 and 3 are perfect. I did not understand the motivation behind the sentiment analysis in Session 2.
Michael Siu –
I like this course but a bit shy of 5 stars. It’s a good course but on the shorter side leaving me wanting a bit more depth into the subject so I can have a more fundamental understanding of the LSTM and maybe how best to tune the hyperparameters. I totally understand this is not a deep learning or neural network course but then those courses don’t relate their use to predicting stock prices and sentiments. These applications are really great concrete examples that makes DL/NN even more exciting. Thank you for a great course! Wish there’s a part 2/advance level.
Christopher Zickler –
Der Kurs war sehr hilfreich, jedoch w re es sch n gewesen, wenn man noch probiert h tte die Genauigkeit zu verbessern indem man vielleicht mehr Epochen trainiert h tte oder mehrere Inputs und nicht nur den Close Price.
Jin Man Lee –
Excellent examples and clearly explained
Alejandro Carranza –
Super bueno y recomendable. El curso es muy pr ctico y explicado claramente con ejemplos reales.
Rekhaks –
Yes perfect
Francisco de Paula –
Muito bom!
Dr.Maitha AlShaiba AlNuaimi –
using good examples and explanation is clear
Suraj S –
This course was a great hands on learning process. I would have liked more explanations on what certain parts (like Keras tokenizer and texts to sequences) do and how the models worked.
Eugenio Boggio –
How to present a prediction that is not working at all as prediction!!
Sai Anirudh Sriram –
Very good course on introduction to predicting stock prices using LSTM. Well paced and easy to follow, understand and implement. Had a wonderful time
Fahad Radhi Al Harbi –
Thank you for the great course and really I learned a lot from this interesting course.
Hubert Plumlee –
My main interest is in the NEW BONUS session of this course. Both in the example given of the bit coins and other stocks I used in this session give a jump between the actual 10 days to the projected next 10 days. Something is wrong that the projected next day results do not match more closely with the last day of the actual. Please review this development and see why these is not a much better agreement in the actual days and the projected days results. Hubert Plumlee hplumlee@yahoo.com
Sten R –
Mir hat der Kurs sehr gut gefallen. Man lernt eine ganze Menge im Bereich Kursprognose und Sentiment Analyse. Der Kurs ist logisch aufgebaut und man kann den einzelnen Schritten gut folgen. Anfragen an den Dozenten werden schnell, sehr kompetent und ausf hrlich beantwortet. Vielen Dank.
Richard Yin –
Unequivocal demonstration and the content is beneficial.
Thomas Marino –
I would recommend an optional module that goes into a bit more detail on how these models work and how to interpret the results. Maybe add a slide deck walking us through the deeper meaning in some of this code. You don’t spend any time explaining what’s happening in your code, where you’re introducing uncertainty with this type of predictive approach, or where the results require further subjective analysis for interpretation. You explicitly market the course as one where students can dive in. This is really dipping toes into the water.
Stefan H ck –
Der Sprecher erkl rt kaum warum er vorgeht wie er vorgeht. Er wiederholt lediglich in W rtern, was er eintippt. Das vermindert das Verst ndnis leider ziemlich stark und l sst sich nicht replizieren. Der Mehrwert ist daher bisher leider nicht gegeben.
Monaem Hosen –
I would suggest everyone enrol in this course. It’s nicely explained in a simple and understandable way. Every concept is taught effectively. Especially He explained every line of code with the explanation.