Run football dataset on Keras
£10-20 GBP
Dibayar semasa penghantaran
First a quick test. Open the test_freelancer.csv. These are stats of football games. When your proposal send me a private message as well with the name of the team that scored the most goals in the entire season and the number of goals . I know the answer, it is just a quick test. Names of the teams appear in the columns home_team_name and away_team_name, the goals they scored are in home_team_goal_count and away_team_goal_count respectively. Each team appears 19 times as home team, and 19 times as away team, I am interested which has the highest sum total.
I have a dataset([login to view URL]) of football games with different attributes and the result of them as the class. The dataset is in .tab format, which are has values delimited by \t. You need to convert the data so that it can be used in Keras and then run a few models on it. I expect a report of the models being run k-fold validation. The code must also include the possibility to run a new case on the best model. Namely, inserting values of attributes and than the selected model returns the predictions.
ID Projek: #25824564
Tentang projek
4 pekerja bebas membida secara purata £41 untuk pekerjaan ini
I am an experienced Data Scientist and Machine Learning Engineer. Data Visualization, NLP, Deep learning, Artificial intelligence, machine learning, Data structures, and algorithms are my major fields. I finished speci Lagi
Hello, I am really interested in your project. Especially I have rich experience in C/C++, Python, Machine Learning Algorithm. If you need, I can show you my previous work. I can work full time in your time zone and I Lagi
Hello, Hope this message finds you well, I checked your details and I believe that my experience is what you are looking 4. I have been working on similar projects for the past eight years, and I have the essential sk Lagi
Hello, I am confident I can build and deliver a good model using the library you are requesting (Keras), so do not hesitate to contact me.
