In our model, this change in ratio resulted in considerable neuronal damage, decreased neural contacts, and memory impairment," Praticò said.
我们的模型表明,EMT并非罕见事件,而是乳腺肿瘤细胞的固有特征。
Our models suggest that EMT is not a rare event but is an inherent feature of mammary tumor cells.".
约8小时后,我们的模型已得到充分训练,马克用FakeApp把我的脸放在高斯林的身上。
About eight hours later, after our model had been sufficiently trained, Mark used FakeApp to finish putting my face on Gosling's body.
我们并不做好莱坞的那些玩意;我们的模型是用于实际工作的,”阿尔德里奇说。
We don't do Hollywood stuff; our models are for actual work,” Aldridge says.
尽管组合稀疏约束迫使我们的模型仅考虑几个特征,但这些特征大部分用于所有任务。
While the group-sparsity constraint forces our model to only consider a few features, these features are largely used across all tasks.
其次,我们的模型是启发式的,因为他们在不断学习和自我纠正,在寻找他们所识别的模式的变化。
Second, our models are heuristic in that they are constantly learning and self-correcting, on the lookout for changes in the patterns they have identified.
我们的模型编织在一起的175个治疗师和治疗师在训练的技能创造关怀的高品质体系-即一个得到的结果。
Our model weaves together the skills of 175 therapists and therapists-in-training to create a high-quality system of care- one that gets results.
我们的模型只包含分为多个类别的功能-例如,“年龄组35-44”,而不是任何人的确切年龄。
And our models only incorporated features grouped into broad categories- for example,"Age group 35-44," rather than any person's precise age.
我们的模型显示,在资源限制方面,专业化的发生是为了帮助整个机构在当前环境参数下更有效率。
Our model shows that in terms of resource constraints, specialization happens so as to help the entire body be more efficient under current environmental parameters.".
此外,赋予我们的模型学习任务层次结构的能力是有帮助的,特别是在需要不同粒度的情况下。
In addition, giving our models the capacity to learn a task hierarchy is helpful, particularly in cases that require different granularities.
预处理我们的数据,以便我们的模型可以在最佳条件下学习.
To preprocess our data, so that our models can learn in the best conditions.
基于这些预测,我们的模型会建议如何提前一天对电网做出最佳的每小时交付承诺。
Based on these predictions, our model recommends how to make optimal hourly delivery commitments to the power grid a full day in advance.
我们需要改进我们的模型,以便我们可以研究这个过程,这可能会产生更大规模的气候影响。
We need to improve our models so we can study this process, which could have larger-scale climate implications.".
要始终让我们的模型更好地运行,一种极简单的方式就是按比例调整计算量”,Karpathy说。
One very easy way of always getting our models to work better is to just scale the amount of compute,” Karpathy said.
These datasets are thought to require multi-sentence reasoning and significant world knowledge to solve suggesting that our model improves these skills predominantly via unsupervised learning.
Now we can use SciKit-Learn's built in metrics such as a classification report and confusion matrix to evaluate how well our model performed.
当与政府和金融领域的客户做生意时,这就是一个很重要的要求,因为我们的模型需要通过合规性检查。
This requirement is important when dealing with clients in government or the financial space since our models will need to be passed through compliance.
一旦我们清楚了请求的到来,我们就可以查看我们的模型是否能够及时地产生结果。
Once we are clear that requests are coming, we can look at whether our model is producing results in a timely manner.
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