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Passa al contenuto principale dei risultati in Scarpe e borse : Borse : Donna : Chicca Borse. Passa ai risultati principali della ricerca. Amazon Prime. Media recensioni clienti.

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Nuovi arrivi. Spedizione Internazionale. Il prezzo e altri dettagli possono variare in base alle dimensioni e al colore. Love Moschino. David Jones. Mario Valentino. Chicca Borse. Miss Lulu. Angel Barcelo. Hai bisogno di aiuto? Visita la sezione Aiuto o contattaci. Torna ai filtri del menu. Consegne illimitate in 1 giorno. Ulteriori informazioni su Amazon Prime. Torna su. Per conoscerci meglio. Metodi di pagamento Amazon. Amazon Advertising Trova, attira e coinvolgi i clienti.

Amazon Music Streaming di milioni di canzoni. Audible Download Audiolibri. Amazon Warehouse I nostri prodotti usati e ricondizionati. Book Depository Libri con spedizione gratuita in tutto il mondo.

Kindle Direct Publishing Pubblica i tuoi libri in formato elettronico. Prime Now Consegna in finestre di 2 ore.

Shopbop Designer, Marche, Fashion e stile. Amazon Business Servizio per clienti business. Amazon Second Chance Regala, scambia, dai una seconda vita.Passa ai risultati principali della ricerca. Amazon Prime. Media recensioni clienti. Selezione di brand. Nuovi arrivi. Opzione di Abbonamento. Il prezzo e altri dettagli possono variare in base alle dimensioni e al colore.

Love Moschino. Miss Lulu. Fino a EUR di buoni regalo con Edison. Prenotazione al prezzo minimo garantito. Mandarina Duck. Calvin Klein. Hai bisogno di aiuto? Visita la sezione Aiuto o contattaci. Torna ai filtri del menu. Consegne illimitate in 1 giorno. Ulteriori informazioni su Amazon Prime. Torna su. Per conoscerci meglio. Metodi di pagamento Amazon. Amazon Advertising Trova, attira e coinvolgi i clienti. Amazon Music Streaming di milioni di canzoni.

Audible Download Audiolibri. Amazon Warehouse I nostri prodotti usati e ricondizionati. Book Depository Libri con spedizione gratuita in tutto il mondo. Kindle Direct Publishing Pubblica i tuoi libri in formato elettronico.

Prime Now Consegna in finestre di 2 ore. Shopbop Designer, Marche, Fashion e stile. Amazon Business Servizio per clienti business. Amazon Second Chance Regala, scambia, dai una seconda vita.He was out of the lineup for the next two games and since then he has been practicing and playing with his left hand in a large, club-like cast. On Thursday, he practiced with less protection on the injured hand, a setup that allowed him to use both of his hands. Those are important assets when it comes to shedding blocks and making effective pass-rush moves.

Just not quite as good as he would without it. With two usable hands, he had 3. Since then, he has played in five games without a sack. Edge rusher Preston Smith had 4. That internal pass rush is hard to replace, quite frankly. Philip Rivers is not a mobile quarterback but he has been sacked only 13 times this year. If a less-encumbered Ioannidis can pick up his game, Smith and Ryan Kerrigan could disrupt the comfortable pocket in which Rovers has been able to operate.

Sign up 10 commits 1 branch 0 releases Fetching contributors Jupyter Notebook 56. At launch, the platform will cover the four major US sports (Football, Basketball, Baseball, Hockey), Soccer and Tennis. Moreover, the models provide stats to measure the performance of the algorithm for the current season (for each sport) along with bankroll comparaison stats with bookmaker (scraping from the oddsportal's website to do so).

Here's below an image from the mobile app propotype based on the platform. This is contrary to another popular method of representing the teams as the favorite and underdog. The point differential is chosen to be positive when the home team scores more points than the away team. To represent the difference between the two teams that are playing in the matchup, the ratio or the difference between the same attributes are taken between the two teams. Therefore, when attributes are a positive indicator of performance, a value greater than 1 indicates that the home team performs better for that particular attribute.

Examples of this are win streak, compared to statistics such as points per game that would be compared by taking the ratio. Web Scraping The data is scraped from several websites according to each sport using Python and the Selenium and BeautifulSoup (only for MLB data) packages for Python.

Data sources for each sports are described in the "Link" section. Game stat data, team stat data, and datetime data are merge later into a feature file (.

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In the same scripts, After having obtained the raw data set, data is cleaned throughout the script. The script checked the completeness and validity of all the data files, and eliminated any CSV parsing errors or erroneous data values.

Here is the main idea: Having validated all our available data, the script then proceeded to load the data from the csv files into an SQL database using the SQLite single-file database engine and a few Python scripts. The flexibility of SQL queries allowed one to easily perform complex joins and merges between multiple tables via the the script. Thus, the script converts the clean scraped data to data structures that the libraries in scikit-learn can easily use.

The ultimate result of the routines included in this file is a numpy array containing all the features and game results for the historical game data. The features have not been normalized but the next script provide one the ability to easily normalize or standardize the data. Algorithm Tuning and Running This step is located in the "RunModelLeague.

A logistic regression predictive model with the L1 penalty is created. Analysis of results are output to csv files. Then, webscraping (through the ScrapeMatchupDatetimeOddsTwoChoicesLeague.

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Thus, the final output give additionnal detail such as odds for both home and away teams, the choice of the bookmaker (e.Example: 128 description optional A description of the model up to 8192 characters long. Example: true name optional The name you want to give to the new model. Example: 10 randomize optional Setting this parameter to true will consider only a subset of the possible fields when choosing a split.

Example: 16 tags optional A list of strings that help classify and index your model. Boosting attribute for the boosted tree. All the information that you need to recreate or use the model on your own. Specifies the list of ids of the field that the model predicts. More concretely, it contains the training data distribution with key training, and the distribution for the actual prediction values of the tree with key predictions.

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Importance is the amount by which each field in the model reduces prediction error, normalized to be between zero and one. Default strategy followed by the model when it finds a missing value. At prediction time you can opt for using proportional. A dictionary with an entry per field used by the model (not all the fields that were available in the dataset).

They follow the same structure as the fields attribute above except that the summary is not present. A Node Object, a tree-like recursive structure representing the model. Method of choosing best attribute and split point for a given node. For classification models, a number between 0 and 1 that expresses how certain the model is of the prediction. See the Section on Confidence for more details.

Note that for models you might have created using the first versions of BigML this value might be null.

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An Objective Summary Object summarizes the objective field's distribution at this node. If the objective field is numeric and the number of distinct values is greater than 32. If the objective field is categorical, an array of pairs where the first element of each pair is one of the unique categories and the second element is the count for that category.

If the objective field is numeric and the number of distinct values is less than or equal to 32, an array of pairs where the first element of each pair is one of the unique values found in the field and the second element is the count. A status code that reflects the status of the model creation.

Example: "000005" boosting optional Gradient boosting options for the ensemble. Required to created an ensemble with boosted trees. Example: 128 description optional A description of the ensemble up to 8192 characters long. Example: flase name optional The name you want to give to the new ensemble. Example: "000003" ordering optional Specifies the type of ordering followed to build the models of the ensemble. Example: 16 tags optional A list of strings that help classify and retrieve the ensemble.

If no significant improvement is made on the holdout, boosting will stop early. This value should be between 0 (inclusive) and 1 (exclusive). Example: false iterations optional The maximum number of boosting iterations to be performed. For regression problems, one boosted tree will be generated for every iteration.

For classification problems, however, N trees will be generated for every iteration, where N is the number of classes. This value should be between 0 (exclusive) and 1 (exclusive). This will be 201 upon successful creation of the ensemble and 200 afterwards. Make sure that you check the code that comes with the status attribute to make sure that the ensemble creation has been completed without errors. This is the date and time in which the ensemble was created with microsecond precision.

True when the ensemble has been created in the development mode.The convenience of not having to research places to stay was the reason that we used Nordic Visitor, for I would not have known where to begin to book guesthouses in some of the remote areas in Southern Iceland.

Hilmar was fantastic - always a prompt email response away - which was another level of convenience that made travelling to a foreign country that much easier. After seeing the photos that we took, I have already recommended Nordic Visitor to three friends just in case they decide to visit.

I can't say enough nice things about my experience with the company. Planning for Iceland was always going to be an issue for my partner and I due to our rather hectic work schedules, fortunately Nordic Visitor took care of everything for us.

It started with a quote that ended up being cheaper than three other competitors we had contacted, for pretty much exactly the same hotels and services. They were very good at tweaking parts of the trip to cater for our needs and went the extra mile in making sure all was the way we wanted it to be. The planning which we received prior to departure, and again on arrival, was thorough and easy to comprehend. Times, schedules and information provided was all well documented and meant we had little to do in the run up to our trip.

We had opted for the self-drive full circle tour of the island and thanks to all the information could easily plan our days.

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The only downside is you do not realise until in Iceland how slow going from A to B can be. The 1 road is certainly not your average motorway, so you need to give yourself plenty of time to get places. It may be a bit confusing to novices who hope to see everything listed in the information booklets. We were particularly happy about the customer care. Although we are a very self sufficient couple, use to tackling more treacherous terrains, it was really nice that Nordic Visitor took time to check-in with us to see that all was going to plan.

The mobile phone given to us came in very handy too. Overall, the only slight problem we faced was with the car rental company for a tiny chip in the windshield which cost us the full franchise.

Our guide was very informative, an excellent driver, and very considerate. The country was fascinating, and with my background in geology I was fascinated to see many things that I have learned about in the past. Overall this trip has been a highlight of our travelling experience. Thank you for the itinerary, and organisation. Everything was very enjoyable and the organisation made the trip a lot less stressful before and during.

The suggested itinerary allowed us to see some of the sights we would not have known to keep an eye out for had we travelled on our own. However, the flexibility of having our own car and keeping to our own agenda also meant that we were able to explore other areas of interest that were not included in the itinerary.

My husband and I had an amazing tour of Iceland. Nordic Visitor provided us with itineraries and vouchers that were very helpful and organized.Our 1st choice was a 1-1 draw.

Match ended in a 0-0 Draw. Our scoreline was 1-1. Worst could be a 1-1 draw. Stayed 3-0 for long. We went for 3-1. Australia won the test by 10 wickets as predicted. We said, 3-1 Monaco win. A difference of 2 goals. Our scoreline of 2-1 Getafe win was correct too. Said, Sociedad wouldn't win. It remained 1-0 till the 90th minute. Hoffeinheim equalized at the edge of the game. Match ended 1-1 as we predicted. Gladbach scored 3 goals quickly.

It stayed 3-1 for long. Game ended, 4-2, Gladbach win. WI scored 356, became 0. Also said, despite starting favs at home, don't see Dortmund having an edge at all. Match ended 3-0 PSG.

Chelsea won in the last moments of the last minute of the game. RomaUEFA Champions League 2017-18 Chelsea vs A. Roma, 18-10-2017Said, no team looks outstanding for this game. Indeed, it ended up in a 3-3 Draw. Asked to lay Pak early(0. Can be better than that.


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