Help: Which ML/DL model aproach is more suitable for my problem.

[enimarix]

I am seeking your advice on the most appropriate machine learning/deep learning model approach for predicting the winner of a Dota 2 game based on a vector of data. The vector will contain features such as team1, team2, hero1, hero2, number of games played with the hero, among others, and a target variable y_train of 0 if team1 wins and 1 if team2 wins

I understand that there are several ML/DL models that could be used for this purpose, such as logistic regression, decision trees, random forests, gradient boosting, and neural networks, among others. However, I am unsure which one would be the most suitable for this specific problem and have the highest chance to predict with good accuracy.

Therefore, I would be grateful if you could share your experience and insights on this topic, and provide any suggestions or recommendations on the most appropriate ML/DL model approach for predicting the winner of a Dota 2 game based on the given vector of data.

Thank you in advance for your valuable contributions.

Best regards,