Stock Level Prediction
₹750-1250 INR / tunti
Here, I have used a Long Short Term Memory Network (LSTM) for building your model to predict the stock prices of Google.
LTSMs are a type of Recurrent Neural Network for learning long-term dependencies. It is commonly used for processing and predicting time-series data.
From the image on the top, you can see LSTMs have a chain-like structure. General RNNs have a single neural network layer. LSTMs, on the other hand, have four interacting layers communicating extraordinarily.
The model considers various aspects to predict the stock market trends .
Projektin tunnus: #38962496
Tietoa projektista
18 freelanceria on tarjonnut keskimäärin ₹1014/tunti tähän työhön
Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including Lisää
Hello, I have read the outline of your project, and I’m sure can solve the task, provide correct result, free revision guarantee. My background is in statistics and applied mathematics using Python/R programming for mo Lisää
Hello, I see you're working on predicting stock prices using LSTM networks. I have experience in developing machine learning models for financial markets, including time-series analysis and neural networks like LSTMs. Lisää
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From Tech Lead: Hi, I've utilized a Long Short-Term Memory (LSTM) network to build a predictive model for Google stock prices. LSTMs are a type of Recurrent Neural Network (RNN) designed to learn long-term dependencie Lisää
Hello, I am excited to submit my proposal for building a Long Short Term Memory (LSTM) model to predict Google stock prices. With my expertise in machine learning and deep learning, I am confident that I can deliver a Lisää
Hi, I am 100% confident in my ability to deliver this project and can immediately showcase a demo of the chatbot I have already developed. With 9 years of experience at Capgemini and TCS, I specialize in AI, Machine L Lisää
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