Meta for Business
Today we’re launching cross-device reporting for Facebook ads, enabling advertisers to see for the first time how people are moving between devices — across mobile apps and the web — before they convert. Imagine seeing an ad for a product on your mobile phone while in line at the bank. Do you immediately make a purchase on your phone? Probably not. But perhaps you go back to your office later that
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We provide the world’s leading digital cross-device graph By creating not only the first, but the most robust global cross-device digital identity graph on the market, Tapad has partnered with brands to maximize their digital marketing investment for years to come. The Tapad Graph enables marketers to identify a brand customer or related household across multiple devices, unlocking key use cases a
DNX Ventures | An Early Stage VC focused on B2B Startups
We partner with teams that are shaping industries and transforming the way we live and work We partner with teams that are shaping industries and transforming the way we live and work. Fund US & Japan We connect two of the most unique and innovative markets by supporting founders in both regions. Investment Early Stage/ B2B Startups We invest in Seed and Series A startups solving the biggest chall
1.1. Linear Models
>>> from sklearn import linear_model >>> reg = linear_model.LinearRegression() >>> reg.fit([[0, 0], [1, 1], [2, 2]], [0, 1, 2]) LinearRegression() >>> reg.coef_ array([0.5, 0.5]) The coefficient estimates for Ordinary Least Squares rely on the independence of the features. When features are correlated and the columns of the design matrix \(X\) have an approximately linear dependence, the design ma
iPython-Notebooks / Comparing machine learning classifiers based on their hyperplanes or decision boundaries.ipynb / Jupyter Notebook Viewer
from pykalman.classifier import GenerativeBayes import pandas as pd import numpy as np rnorm = np.random.normal from sklearn.svm import SVC from sklearn.tree import DecisionTreeClassifier from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier from sklearn.qda import QDA from sklearn.linear_model import LogisticRegression from sklearn.neighbors import KNeighborsClassifier from skle
Newsroom - Gartner
Gartner Survey Reveals 71% of CMOs Believe They Lack Sufficient Budget to Fully Execute Their Strategy in 2023 Marketing
機械学習CROSSをオーガナイズしました - Preferred Networks Research & Development
もう豆まきしましたか？比戸です。 1月17日に、エンジニアサポートCROSSで機械学習のセッションをオーナーとして主催させて頂きました。今回はその報告と内容のまとめをさせて頂きます。 エンジニアサポートCROSSは今年で3回目を迎える、主にWeb系のエンジニアが集まる技術イベントで、今年も800人以上が集まったそうです。すごいですね。 並列開催されるパネルディスカッションを基本とするイベントで、有名なWeb関連サービスを持っているわけではないPFIの私がオーナーということで、持てる人脈をフル活用してパネリストをお願いしたところ、お声がけした方全員にご登壇いただけることになりました。 Yahoo!JAPAN研究所 田島さん 楽天技術研究所 平手さん ALBERT 小宮さん FFRI 村上さん 産総研 油井さん Gunosy 福島さん 大手Web企業から尖ったサービスの会社、アカデミア周辺まで
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SOS SMS - Red Cross
WPP Forms Cross-Agency Team To Service Aston Martin
The Trueffect Blog - Trueffect
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