34
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Budget: 27000 UAH Deadline: 7 days
Good day! I develop in Python, have worked on similar projects with React/Node.js, and am ready to collaborate.
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Budget: 27000 UAH Deadline: 7 days
Hello, I worked on time series analysis for a fintech company — finding patterns in binary sequences of transactions (prediction accuracy +68%, dataset 2M+ records).
Interesting task! Let me know — is the sequence generated algorithmically or are these real data (for example, trading or game results)? This will immediately determine the choice of research methods.
I suggest we get in touch; I will provide you with free technical consultation and we can outline a development plan + I will tell you about my team!
Budget: 27000 UAH Deadline: 7 days
Hello, Sergey! This is literally my area of expertise. I am studying at Lviv Polytechnic in the specialization "Artificial Intelligence Systems." We have studied similar tasks in detail as part of our coursework on optimization methods and data analysis (modeling hidden Markov chains, stochastic processes, and estimating mathematical expectations over long distances). I would be happy to take on this research.
How I will implement the task in Python to avoid overfitting and find a real stable signal:
Statistical screening (Base): Analysis of 0/1 frequencies, calculation of the autocorrelation function (ACF) to identify lags, testing the hypothesis of randomness (Runs test).
Contextual analysis (N-grams): Searching for fixed-length patterns (sliding window from 2 to 8 characters). We will build conditional probabilities: if string $P$ appears in the dataset, what is the actual probability $P(1|P)$. We will filter patterns where the probability bias is statistically significant (above 55–60%) and calculate the p-value to cut off random noise.
Modeling: I will check the predictive power of simple Markov models as well as lightweight ML algorithms (we will convert the sequence into tabular features with lags and train Random Forest / XGBoost with strict regularization).
In the end, I will provide:
Fully reproducible clean Python code (Jupyter Notebook) with a split into Train / Test samples (to prove that the model actually works on new data).
A step-by-step report describing the methods used, a list of profitable patterns found, a final Score according to your system (+1/-1), and an assessment of the mathematical expectation.
I would be glad to dive into the task. Message me privately, and I will share my initial thoughts on the dataset, and we can start working!
10
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Budget: 27000 UAH Deadline: 8 days
Hello. To identify patterns in a binary sequence, I plan to apply a multi-step approach that includes deep statistical analysis, feature engineering from the sequence history, and exploration of various predictive models. This will encompass methods for pattern and anomaly detection, the application of Markov models, as well as machine learning tools such as tree-based classifiers or basic recurrent networks to identify states with a high probability of the next symbol. The key will be not just to find correlations but to create a robust model capable of reliably demonstrating positive mathematical expectation on unseen data, using cross-validation and thorough backtesting. I have significant experience in time series analysis and uncovering hidden dependencies, which will allow for the effective use of already developed algorithms and templates to accelerate the development and validation of solutions. I suggest discussing all implementation details, final budget, and timelines in private messages.
57
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Budget: 27000 UAH Deadline: 5 days
I work as a financial analyst in a large international company. I have experience with similar projects. I can help.
Budget: 27000 UAH Deadline: 5 days
Hello, I am very interested in the project. I have previously worked with neural network training and data analysis, so I have experience. I am ready to discuss the budget in private messages.
40
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Budget: 27000 UAH Deadline: 7 days
Hello, Sergey.
I can conduct a sequence analysis as a full statistical analysis, not just model fitting. I will check if there is a stable signal in the data: frequencies 0/1, series, n-grams and contexts, states before the next character, autocorrelations, as well as simple statistical and ML models.
I will present the results reproducibly:
- Python code for the analysis;
- splitting the data into training and testing parts;
- a list of identified patterns, if they hold statistically;
- accuracy, number of predictions, and final score based on the system +1/-1;
- a brief report: which approaches worked, which did not, and where there is a risk of overfitting.
An important point: if the sequence turns out to be close to random, I will also show this through tests, so as not to present a random coincidence as a pattern. If there is a signal, I will describe it as a clear rule or model that can be further tested on new data.
Deadline: up to 7 days.
52
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Budget: 27000 UAH Deadline: 4 days
Good day
I am ready to take on this work
Feel free to write, I will be happy to help with your task as much as possible
I am waiting for further communication in private messages
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